This paper presents fabric-based soft robotic modules with primitive morphologies, which are analogous to basic geometrical polygons—trilateral and quadrilateral. The two modules are the inflatable beam (IB) and fabric-based rotary actuator (FRA). The FRA module is designed with origami-inspired V-shaped pleats, which creates a trilateral outline. Upon pressurization, the pleats unfold, which enables propagation of angular displacement of the FRA module. This allows the FRA module to be implemented as a mobility unit in the larger assembly of pneumatic structures. In the following, we examine various ways by which FRA modules can be connected to IB modules. We studied how different ranges of motion can be achieved by varying the design of the rotary joint of the assemblies. Using a state transition-based position control system, movement of the assembled modules could be controlled by regulating the pneumatic pressurization of the FRA module at the joint. These basic modules allow us to build different types of pneumatic structures. In this paper, using IB and FRA modules of various dimensions, we constructed a soft robotic limb with an end effector, which can be attached to wheelchairs to provide assistive grasping functions for users with disabilities. Euclid’s Elements by Euclid of Alexandria, various types of polygons exist to describe shapes of different forms, and the simplest one of them all would be trilateral polygon, an amalgamation of which can be used to derive more complex polygons [Geometry—the study of points, lines, and angles—is an extensive branch of mathematics that is deeply ingrained in our daily lives and the objects that surround us. Shape is one of the most basic ways by which we identify and characterize objects. According to the book of polygons . It is ipolygons  to pyrampolygons , the strFluidic elastomeric actuators (FEAs) of soft robots are commonly designed to be expanded or elongated in shape, with an internal pneumatic chamber . Upon prIn addition, modular soft robots have also been developed for various applications and actuation forms ,15,16,17Modular soft robots were previously discussed by Onal and Rus, who designed and fabricated FEA modules, which can be arranged in serial, parallel, and hybrid configuration . HoweverIn this paper, a simple modular design concept is adopted, whereby triangular and rectangular shape primitives are introduced—the inflatable beam (IB) module and fabric-based rotary actuator (FRA) module. Fabric material is used to fabricate these soft pneumatic actuator modules. Fabric-based soft actuators have begun to emerge lately for various applications, such as robotic grippers or wearable rehabilitation devices . The thiTwo actuator shape primitives were designed—the IB module and the FRA module . The IB Fabric was used to fabricate the modules and it was coated with thermoplastic polyurethane . By inducing heat or ultrasonic acoustic vibrations on multiple layers of stacked fabrics, the polyurethane coating on the layers will melt and be welded together. In this way, airtight pneumatic structures can be formed. However, the fabric materials are not of hyperelastic nature, as compared to the rubber elastomers that are used to develop soft robotic structures in previous works. Hence, when deactivated, the fabric-based module takes longer to return to its default state. Therefore, to solve this limitation, the FRA module was fitted with a C-shaped frame d, which FRA modules and IB modules can be assembled in various configurations. The basic assembly would consist of a single FRA module and two IB modules which would be denoted as SNG assembly in subsequent sections b–e. InteWrinkling effect is a common phenomenon in textile-based pneumatic structures, which subsequently affects the stiffness of the structure and its load supporting capacity. Wrinkling occurs on the concave side of the inflated textile structure, where the textile is unable to resist compressive loads. In the wrinkled region, the bending stress due to the applied moment equilibrates axial stress in the textile layer . In thisThe displacement characteristics of assembled modules due to pneumatic pressurization of the FRA module would vary based on the number and configuration of FRA modules at the joint. Hence, it is essential to understand the range of motion of assemblies of different configurations  . Based oJoint stiffness of assembly is introduced by the intrinsic resistance of the FRA module to rotational efforts caused by pneumatic pressurization. The joint stiffness is obtained by measuring the passive torque output of the assembled modules at different actuation angles. SNG assembly with a single FRA module is loaded onto the test platform, whereby the IB module at one end of the assembly is fixed and the second IB module at the other end is moved to specific joint angles , during The load bearing capacity of the IB module is independent of inflation pressure during the initial unwrinkled phase. Hence, the slope of the regression line, which relates deflection of the IB module with respect to applied load, remains the same for different pneumatic pressures . HoweverAngular displacement of assembled modules is generated by the unfolding action of the joint FRA module. SNG assembly exhibits higher angular displacement compared to assemblies with double FRA modules (SRS assembly and PLL assembly). For the SNG assembly, maximum angular displacement (124.86 ± 0.50°) is reached at 30 kPa, beyond which a plateau is observed upon further increment in pneumatic pressure . This isThe morphology of the actuated FRA module is assumed to adopt a simplified outline with resemblance of a triangle. Upon pressurization, the unfolded section of the inner fabric layer forms a triangular outline with the outer fabric layer. As the FRA module expands upon pressurization, the outline of the module also increases with pneumatic pressure. The unfolding action of the activated FRA module causes a respective change in the angulation. It is assumed that the external fabric layer is inextensible and that during the initial unpressurized state, the external and internal layer form rectilinear edges. 1 and P2 refer to pressure along the inner surface of FRA during the equilibrium state. PF is pressure applied along the inner folded edge to generate pushing force, which causes the FRA module to unfold. B0 is the breadth of the inner fabric layer of the FRA module. BP is the length of the inner layer, which is unfolded at current pneumatic pressure (ΔP), whereas BP-1 is the length of the inner layer, which has previously been unfolded at lower pneumatic pressure. E refers to Young’s Modulus of fabric [ΔP is pneumatic pressure supplied to the FRA module. Pf fabric . α referp is the length of the inner layer, upon which pushing force is concentrated to cause unfolding of FRA. tp is assumed to be of minimum length of 0.4 mm, which is the thickness of the fabric. The range of motion of the FRA module is limited by the amount of fabric within the pleat and the inherent resistance of the Ninjaflex endoskeleton. The inner folding of fabric and Ninjaflex endoskeleton of the FRA module provides resistance to the unfolding motion of the module. This enables the module to resume its initial angle at an unactuated state. In an assembled modular structure, resistance to deformation may vary based on the number of FRA modules attached at the rotary joint. As seen in t0 is the length of the inner fabric layer of the FRA module. θP refers to angular displacement of the FRA module. κeq is the equilibrium stiffness of the rotary joint of the assembled modules, whereby κ1 and κ2 refer to the stiffness of the FRA modules in the rotary joint. In intermediate rotary joint assemblies, two identical FRA modules were fabricated, whereby κ1 = κ2. LA state machine was developed as a position control system for the assembled modules, whereby pneumatic pressure within the FRA modules at the rotary joint is regulated to control the position of the linked IB modules. Zhao et al. developed state machine controllers for the elastomeric fingers in the soft orthotic glove , wherebya, Kb, and Kc). Ka determines the acceptable margin of error for ε. Kb and Kc determine the allowable threshold of the error margin. In the following test, the control parameters were selected to be as follows: Ka = 0.05, Kb = 0.01, and Kc = −0.01. When the error thresholds are exceeded, the controller would switch to either an “in” or “out” state, and inflation and deflation of the actuator occur accordingly. At each control state, the opening and closing duration of respective valves are controlled using pulse width modulation, the duty cycle of which is varied based on the preset time variables (X and Y).The state machine controller was designed with five control states, each of which requires different actions of the two valves in the integrated valve system . TransitAn inertial measurement unit (IMU)  was used to provide sensor feedback for the measured angle of the IB module that is linked to the actuating FRA module. The IMU is placed at the distal end of the freely moving IB module along the central axis. By tracking the orientation of IMU, the angle of the actuating IB module can be tracked. Due to the actuation form of FRA, the movement of the attached IB module would be assumed to be a single plane and that the movement of the assembled modules would be minimal in other planes. Hence, based on the orientation of IMU on the actuator, the estimated roll angle of IMU output data is used to provide joint angular displacement feedback to the state machine.Assembly with FRA modules in parallel configuration (PLL assembly) was chosen to analyze the step response of the position controller . For theAmidst steady state oscillation, a higher magnitude of oscillation is observed at lower reference angles (20°and 25°) than at 30°. This is because the pneumatic source is supplying air at 35 kPa. Hence, when the inflating valve opens, the inflow of air within the actuator is at 35 kPa, which would cause the actuator to displace at a higher angle than the expected value. An inner pressure control loop would have to be included to automatically adjust the supplied pressure of the pneumatic source.Based on the characterization tests, a trade-off exists regarding the range of motion and joint stiffness for the different module assemblies. Hence, to construct larger pneumatic structures, the most suitable form of assembly would have to be chosen based on the requirement of the end structure. The following demonstrates a possible application of pneumatic actuator modules in the construction of soft robotic limb—also known as textile-based robotic arm (TERA). Previously, Otherlab developed a soft robotic limb, which was designed with bellow shaped joint actuators. The multiple folding of the bellow shaped actuator makes the actuator prone to wrinkling effect, which can reduce the stiffness of the actuator and its ability to support load . TERA isHence, when paired in parallel configuration, the FRA modules would be fitted evenly to the adjacent IB modules. This is to ensure uniform transmission of force by the actuating FRA module in the rotary joint to the linked IB module, therefore maximizing the range of motion of the structure. The two pairs of FRA modules in the rotary joints are arranged in different orientations. Activation of FRA modules at different joints would enable movement of the robot along different orientation planes, therefore increasing the degree of freedom. Reversible linkage is formed between FRA modules and IB modules using cables. Each module is fabricated with excess fabric perimeter at either end of the module, which is perforated to create paths for weaving of interconnecting cables between adjacent modules. Should the design require alteration, the interlacing cables can be removed, and the affected modules can be rearranged to the desired conformation. As opposed to the usage of parallel configuration, the end effector of TERA is designed with two sets of FRA modules in series configuration , wherebyCompared to existing similar rigid robotic arms, a soft robotic arm can be made at lower cost and greater ease of fabrication. As it is mainly made with nylon fabric and actuated with air, the soft robotic arm is also much lower in weight. However, the payload of the soft robotic arm is smaller than that of a rigid robotic arm. Nevertheless, due to its lightweight and intrinsic soft nature, the soft robotic limb can be integrated onto structures such as wheelchairs and be deployed in close proximity with human users.To give a new perspective to the conventional design and way of fabrication, we opted to design soft pneumatic modules with morphological resemblance of basic polygons of three-sided and four-sided figures—triangle and rectangle. A simplistic modular approach was adopted whereby two shape primitives were introduced—the IB module and the FRA module, which are fabricated with thermoplastic polyurethane-coated fabric. The rudimentary polygonal outline of modules enhances their versatility, for it permits construction of larger pneumatic structures of more complex shapes and actuation modes through selective congregation of multiple modules. The contributions of the paper are as follows: (1) A simple modular design concept using shape primitives that are inspired by basic geometrical polygons, and (2) construction of larger pneumatic structures using fabric-based modules, which can be assembled and disassembled. Module-based construction of pneumatic structure requires lower volume of operating fluid to function and is able to operate within a lower range of pneumatic pressure, compared to continuum actuators. Reconfigurable fabrication allows the usage of the same designs of actuators to construct more than one type of pneumatic structures. The versatility of the modules was illustrated by the construction of a soft textile-based robotic arm (TERA) with two rotary joints and an end-effector, all of which were developed using the two essential modules. TERA is a lightweight, mobile system which can be attached to objects such as wheelchairs for the disabled to assist with grasping tasks.


This article presents a new approach to the estimation of shift and rotation between two images from different kinds of imaging sensors. The first of the image is an orthophotomap that is created using optical sensors with georeference information. The second one is created utilizing a Synthetic Aperture Radar (SAR) sensor.The proposed solution can be mounted on a flying platform, and, during the flight, the obtained SAR images are compared with the reference optical images, and thus it is possible to calculate the shift and rotation between these two images and then the direct georeferencing error. Since both images have georeference information, it is possible to calculate the navigation correction in cases when the drift of the calculated trajectory is expected. The method can be used in platforms where there is no satellite navigation signal and the trajectory is calculated on the basis of an inertial navigation system, which is characterized by a significant error. The proposed method of estimating the navigation error utilizing Affine Scale-Invariant Feature Transform (ASIFT) and Structure from Motion (SfM) is described, and techniques for improving the quality of SAR imaging using despeckling filters are presented. The methodology was tested and verified using real-life SAR images. Differences between the results obtained for a few selected despeckling methods were compared and commented on. Deep investigation of the nature of the SAR imaging technique and noise creation character allows new algorithms to be developed, which can be implemented on flying platforms to support existing navigation systems in which trajectory error occurs. Over recent years, supporting navigation systems has become particularly important for several reasons. Firstly, the aim is to increase the precision of ammunition and flying objects. Secondly, it is necessary to create systems that can work without the support of GNSS . The lack of a GNSS  signal is a significant limitation whose probability of occurring increases due to potential international conflicts, as well as the possibility of the GNSS signal being jammed or interrupted. For these reasons, it is necessary to create independent systems that allow navigation in the absence of a satellite signal. One of the basic sensors that allows the navigation of objects is the inertial navigation system (INS). However, due to the significant drift and error increasing with time, inertial navigation requires additional systems. Currently, drift is reduced using GNSS systems; however, due to the limitations mentioned above, it is necessary to use additional sensors to support inertial navigation.In the literature, several solutions have been proposed that allow the navigation of objects in the absence of a GNSS signal. The least effective solutions are purely vision methods, which are ineffective in the case of night missions, cloud cover, fog, smog, or smoke. Other remote sensing methods that do not use sensors working in the visible spectrum are used more often. Such solutions use sensors such as light detection and ranging (LIDAR) and an altimeter, which allows a terrain contour (DEM) to be obtained, and then compares the acquired contour with the data in the database. Such systems, also known as Terrain Contour Matching (TERCOM), are utilized to navigate unmanned aerial vehicles or cruise missiles in cases when a GNSS signal could be unavailable ,2,3.A recently developed technique is the use of Synthetic Aperture Radar (SAR) and Interferometric SAR (InSAR) radar for navigation correction ,5,6,7. RThe process of image registration refers to the alignment of two or more images of the same scene which might be obtained with the same sensor, time, and imaging conditions, as well as by different sensors and viewpoints. The process of orientating optical and SAR images is still an open issue, which creates many challenges ,17,18,19The proposed methodology of the automation of SAR data registration with orthophotomaps as well as the SAR trajectory improvement, is a multi-stage process. This process is based on the original software and it consists of: (1) SAR data conversion to the raster form with a georeference file; (2) the aligning of orthophotomaps with a SAR raster based on the extended version of the ASIFT algorithm; (3) the relative orientation based on the classical SfM and modifiedIterative Closest Point (ICP) approach; (4) the analysis of the quality of the relative orientation of processed data; and (5) the final bundle adjustment.In this investigation, the process of optical and SAR images was tested and validated with a high resolution SAR and orthophotomaps from altitude. It should be stressed that the entire investigation was performed on the full resolution of the images, and additionally tested on other pyramid levels. The authors decided to use a well-known SfM approach, but with the following modification: (1) the pre-processing of SAR data with different speckle noise reduction filters in order to increase the possibility of detecting and matching robustness corresponding points; (2) reducing the values of affine angle in the ASIFT algorithm—the values being related to the angle of the antenna; and (3) using a two-stage ICP procedure to eliminate the outliers and compute the correction parameters. Thanks to the use of the ASIFT algorithm, it was possible to detect well-distributed keypoints in the whole area under investigation. The authors decided to eliminate the description and matching step and replace it with the ICP alignment. This allowed keypoints to be treated as a point cloud, and minimize the distance between these two point clouds in an iterative process with the simultaneous correction of translation and rotation of SAR data.The keypoints distributions on SAR images and orthophotomaps.The influence of the SAR image correction on the quality and number of the keypoints.The number of detected keypoints used in the final cooregistration process.The orientation accuracy of marked check-points.In Generation of the SAR raster with georeferences based on the trajectory information.This step is one of the most important parts in the whole automatic registration process. It influences both the computation time and convergence of the ICP process.Pre-processing of SAR data to reduce the influence of the noise.RAW dataMultilook-2D filterAveraging filterMinimum Mean Square Error filterEnhanced Lee filterGamma MAP filterSAR Block Matching 3D filterSelection of the part of the orthophotomap which approximately covers the SAR image, based on the SAR footprint extended by 50 m in each direction.Detection and matching of the keypoints using the modified ASIFT algorithms in the SAR images and orthophotomaps:4.1.1/2, 1/4, and 1/16 of the full resolution of the raster)—ASIFT algorithm.Detection of keypoints in RAW SAR images on three pyramid levels —ASIFT algorithm.Detection of keypoints in SAR images with the speckle noise reduction parameters: 1, 4, 8, and 16 levels —ASIFT algorithm.Detection of keypoints on orthophotomap levels .The presented technique was intensively tested, validated, and compared with the methods existing in the literature. Especially two approaches were investigated ,17. HoweModern software packages, application, and function libraries dedicated to raster data orientation, and 3D shape reconstruction utilize algorithms based on a combination of methods commonly applied in Computer Vision (CV) and conventional photogrammetric approaches. These types of algorithms and methods allow the geometry and appearance of an object or an entire scene to be captured, and have been used in video games assets , virtualThe feature extraction process is the first step of the SfM pipeline, which is based on detectors. For each image (raster data) given as an input, a group of characteristic points  are detected (excreted) based on the local characteristic of the image intensity. For feature extraction, different methods and algorithms can be used which affect the robustness of the detected features, as well as the efficiency of the matching method. Nowadays, two types of commonly used algorithms are corner  and blob detectors  ,36,37,38u is a digital image; T and A are, respectively, a plane translation and a planar projective map due to the camera motion; A, The SIFT  algorithm, which was originally proposed by Lowe  for the n value equals 5, which results in the tilt being simulated 32 times [It is possible to prepare the decomposition of the camera motion parameters into the viewing point angels  might be threaded as a tie point, the feature matching process is used. This allows one to take into consideration two points from different images, but which are characterized by the same description as a homologous point. Different strategies can be used for effectively computing matches between images, but two which are usually used are: approximate nearest-neighbor-based point matching  and brutR is a rotation matrix, When considering two datasets, it is possible to determine interrelations between them expressed by the phenomenon:Equation ) functioIn each of the iterations of the ICP algorithm, the transformation can be determined using the four main methods: SVD decomposition , Hora quSpeckle noise is a common phenomenon that accompanies all coherent imaging systems, such as SAR sensors [speckle has a multiplicative nature, thus SAR imagery is characterized by strong intrinsic noise . Typically, for a single-look SAR image, ISNR  = 0 dB, and we have the same amount of signal and noise power/level. It appears in the image as strong fluctuations in its brightness, hardening the image interpretation.Because all kinds of algorithms which detect keypoints such as ASIFT/SIFT/SURF work on intensity images, the presence of speckle noise in SAR images is an obstacle. Speckle noise affects the behavior of keypoint detector algorithms, which is why it has to be reduced.  sensors . The souAs described in the literature, utilizing SAR radar images for different purposes often requires additional operations, increasing SNR. If the operations are not performed, the results can be strongly disturbed ,61. Somespeckle  or intensity (L is the number of (multi)looks/averages; and m is the statistical moment order . The gaFrom Equations  and 7),,7), provspeckle noise level is the pre-processing of SAR imagery with despeckling filters. Commonly, a classical multilooking technique is applied. Nevertheless, there are plenty of filtration/despeckling algorithms.The authors decided to describe types of filters which were used in experimental processing since the results are different for each filter type.One of the basic ways to deal with the problem of high speckle reduction can be made with less degradation of the image spatial resolution at the same time.In contrast to the classical multilooking procedure , Multilodespeckled (reconstructed) SAR image; L is the number of (multi)looks...The idea for the 2D multilooking procedure was taken from optical image processing. The algorithm operates on the entire, already prefocused SAR image, based on Fourier domain processing.L sub-bands  SAR image; N is the filter window size in pixels/pels, e.g. i is the filter window linear index One of the simplest noise filtration techniques is averaging image samples over the area around a pixel, combined with a sliding window technique (see Equation ). For a N is the number of pixels in the filter window. Note that in extreme cases, if the window size is As a result of the averaging filtration, the speckle standard deviation is reduced by a factor of speckle within the analysis window. One approach to such an adaptive filter is to provide a model-free minimum mean-square error (MMSE) filter based on measured local statistics. The solution of minimizing the mean square error for a pixel k is the linear image pel index (despeckled (reconstructed) SAR image; The above-mentioned despeckling filters fail when the assumption of constant pixel value within the filter window breaks down. The filter should then adapt to take account of excess fluctuations compared to Equation ) so thatEquation ); z˜(k) As can be seen, it is a weighted sum (or linear interpolation) between the mean and given/current pixel value. In cases when there is no fluctuation coming from the image texture, the weighting factor speckle component k is the linear image pel index (despeckled (reconstructed) SAR image; An approach presented by Lee  considerEquation ), but thEquation ); z˜(k) speckle, i.e. speckle. If pixel value speckle contribution to the target when making the filtration, corresponding to treating the bright pixel as a point target that would not give rise to speckle fluctuations. The result of filtering a real-life SAR radar image with an enhanced Lee filter is shown in When there is no image texture variation, it would be expected that the estimate speckle follows a Gamma distribution (Equation (k is the linear image pel index (despeckled (reconstructed) SAR image; The Gamma filter is a Maximum A Posteriori (MAP) filter based on a Bayesian analysis of the image statistics. It assumes that both the SAR image texture and the Equation ). The imEquation ); z˜(k) speckle, it would be expected that speckle. In this case, excess pixel value In the case of pure despeckled (reconstructed) SAR image in WT transform domain; speckle noise ; hard thresholding, and inverse UWT; andaggregation—all filtered blocks are suitably weighted, giving a coarse estimate of the image.The first stage comprises three steps:grouping—blocks are located based on the coarse estimate provided by the first stage;collaborative filtering—each 3D group (of noisy blocks) undergoes WT((Decimated) Wavelet Transformation); Wiener filtering, and inverse WT; andaggregation—as in Stage 1, giving a final estimate of the image.The second stage also comprises the same three stages, but with the following differences:The presented filtration algorithm comprises several state-of-the-art techniques, thus giving better performance in terms of signal-to-noise ratio and perceived image quality than any of the other aforementioned filters. The result of filtering a real-life SAR radar image with the SAR-BM3D filter is shown in In this subsection, SAR image despeckling filtration results are presented and compared. The image used is shown in MATLAB ® m-scripts, and the entire processing chain was made in this computing environment. Thus, the filtration performance in terms of absolute processing time is not meaningful. However, it reflects the computational complexity for each filter.It should be emphasized that the implementations of filters were made as so-called Cuda).From the results presented in ding see g. Howevespeckle reduction and execution time , which significantly affected the focusing of the detected keypoints in the most dynamic regions. The keypoints distribution corresponds to the results obtained for the different despeckling methods previously presented (including the number of detected keypoints). However, fewer keypoints were found in comparison to the previously presented outcomes (apart from the GMAP filter). The algorithm detected Thanks to the reduction of speckle noise, negligible improvement was obtained, which affects the unequivocal shift estimation. The correction distribution, presented in Figures provided for this subsection are attached in Each of the applied filters allowed estimationcorrections to be calculated in accordance with the assumptions. Due to the different nature of the creation of optical images and SAR, some imperfections are visible, but they are negligible in the analyzed problem. The filters processing performance is presented in As can be seen, similar results were obtained for all filters tested. The outcomes of the rotation estimation are characterized by the following relationship: the greater is the number of points found, the greater is the rotation correction determined. Interestingly, the calculation time is not strongly dependent on the number of keypoints detected. However, storing points requires more memory, and, even if the calculation time is similar, the memory required is larger for the method detecting a greater number of points. It should be noted that all computation was performed on the CPU without any parallelization. To decrease the computation time and boost the computation speed, a GPU should be used.The experiments proved that the proposed method for the geometrical matching of SAR and optical images utilizing ASIFT features for SAR-based Navigation Aided Systems is suitable for compute the corrections to the SAR images’ direct georeferencing. In the literature, there are many methods and algorithms for this type of data co-registration ,16,18,19In c is the speed of light and B is radar signal bandwidth. For the proposed method to make sense, high resolution radars should be used, which, unfortunately, are associated with a greater financial outlay and a requirement for high processing power of the computing unit. In addition, it should be taken into account that the obtained high resolution radar images must be filtered to reduce speckle noise, which limits the resolution of the entire imaging. Moreover, phenomena such as heterogeneous movement of the radar carrier platform or changing its speed during the flight in an unpredictable way also degrade the quality of the image. Nevertheless, taking into account and minimizing such phenomena, it is possible to use the method proposed by the authors, which was proved experimentally.On the basis of the results obtained, the calculated correction value per kilometer can also be estimated. Assuming that filter SAR images;find keypoints on SAR and optical images;find shift and rotation correction between images; andcalculate navigation correction between an acquired SAR image and a reference optical image.Combining such methods in a single solution is a novel approach proposed by the authors. Taking advantage of several techniques, an innovative algorithm was proposed, tested and validated to confirm its usability for SAR images obtained during a measurement campaign. This solution may be useful in military and civilian applications, when the lack of a GNSS signal is a critical problem which makes flying missions impossible. Merged techniques such as ASIFT-based keypoint extraction and SfM-based keypoints matching make this method robust and resistant to noise and interference. Thus, the presented methodology can be successfully integrated with existing systems to enhance their precision and dependability. Additionally, the authors provide a comparison of several filters, including their computational complexity and performances. This presents a wide variety of uses for this technique depending on the solution. In the future, the authors intend to implement the method on a real-time platform and test and verify the proposed methodology in real conditions, which should confirm its usability. The target platform is the GPU (Graphics Processing Unit), allowing fast computing to be obtained (both SAR processing and correction estimation). Another crucial issue is the implementation of the functionality that would be able to cope with the situation where the imaged scene has been significantly changed compared to the one that was saved in the database . Such a situation may arise when, for example, the imaged area has been damaged as a result of a disaster or war, and the database on board the flying object does not have current pictures. The estimation may then be ineffective, which is undesirable. This is currently the main problem the authors are working on.This paper presents a novel algorithm for navigation correction estimation dedicated to flying platforms  in cases when satellite navigation systems are unavailable. This method utilizes various techniques to:


An advanced driver-assistance system (ADAS), based on lane detection technology, detects dangerous situations through various sensors and either warns the driver or takes over direct control of the vehicle. At present, cameras are commonly used for lane detection; however, their performance varies widely depending on the lighting conditions. Consequently, many studies have focused on using radar for lane detection. However, when using radar, it is difficult to distinguish between the plain road surface and painted lane markers, necessitating the use of radar reflectors for guidance. Previous studies have used long-range radars which may receive interference signals from various objects, including other vehicles, pedestrians, and buildings, thereby hampering lane detection. Therefore, we propose a lane detection method that uses an impulse radio ultra-wideband radar with high-range resolution and metal lane markers installed at regular intervals on the road. Lane detection and departure is realized upon using the periodically reflected signals as well as vehicle speed data as inputs. For verification, a field test was conducted by attaching radar to a vehicle and installing metal lane markers on the road. Experimental scenarios were established by varying the position and movement of the vehicle, and it was demonstrated that the proposed method enables lane detection based on the data measured. An advanced driver-assistance system (ADAS) assists a driver in dangerous situations that may not always be recognized by a human driver or a self-driving system. Among the many functions of ADAS, the lane departure warning system (LDWS) and lane keeping assistant system (LKAS) help in safe driving by assisting the driver in case of an unintended departure from the lane. Although the LDWS is a warning system, the LKAS is a more advanced system that has the ability to maintain the lane through steering wheel control in conjunction with the control system. A system that assists in lane keeping helps tremendously in accident prevention and is an essential function for autonomous driving technology in the future.The most critical factor in successful implementation of any lane keeping technology is lane detection. Currently, the most widely used sensor for lane detection is a camera. Lane detection technology using cameras has been mainly studied to increase its recognition rate in complex environments ,2,3,4 anIn addition to cameras, light detection and ranging (LiDAR) systems and radars have also been proposed as sensors for lane recognition ,11,12,13As discussed above, cameras play a major role in lane detection. However, in a real road environment, there arise some situations wherein lane detection via cameras is difficult such as when the lighting changes suddenly, when direct sunlight hits the lens, or when there is fog. Hence, radar and LiDAR were investigated for lane detection. Even though LiDAR works well with rapid lighting changes, lane detection is still difficult in fog or in direct incident sunlight. In such environments, radar is a good alternative sensor. Radar is slightly ineffective while detecting the position of the lane in comparison with cameras or LiDAR, but it can at least confirm the existence of a lane; thus, it can be used to detect lanes in situations where cameras or LiDAR are difficult to operate. In this study, we propose a new lane detection method using impulse radio ultra-wideband (IR-UWB) radars to contribute to the determination of lane departure in situations where camera and LiDAR do not function well. The IR-UWB radars have a high-range resolution, because they transmit short pulses at the nano- or picosecond . The higIn this paper, we propose a lane detection method based on IR-UWB radar with characteristics that are suitable for near-lane recognition. Lane recognition requires the presence of objects with a higher reflectivity than the road surface. In our proposed method, metal plates with the same width and length as the lane markings were installed at regular intervals over the actual lane markings, while the radar was directed toward the road surface. The thickness of the metal plates does not affect the radar reflection, so they could be very thin. However, they should be sufficiently robust to withstand being repeatedly run over by vehicles. In addition, most metals are excellent radar signal reflectors with a higher reflectance being advantageous for lane detection. To prevent noise signals from other than the lane, the detection range was set to a distance where the lane was expected to be detected and the lane reflection energy was in the detection range. The detected energy was a signal reflected from the road surface and the metal lane, and the lane candidate group was selected based on the energy difference. The energy detector output of the lane reflector installed at regular intervals repeated the strength and weakness of the signal periodically. The lane interval was calculated using the estimated period and vehicle speed information, and finally, the existence of lanes was determined. A field experiment was performed to verify the proposed method. To this end, a radar was attached to the rearview mirror of the vehicle and metal lanes were installed at regular intervals and lengths in the same position as the existing lanes. Experimental scenarios were established, and actual data were acquired according to the movement of the vehicle in the lane. Based on the measured data, the proposed method successfully detected lanes and verified whether lanes can be maintained or departed.kth radar scan is given as follows when the transmission pulse x(t) is received as The proposed lane recognition system model using IR-UWB radar is shown in In this section, we discuss the workflow for lane detection shown in x and y coordinates  with the value of Equation (9), the areas 1–4 have the same area, but Equation (8) is closer to the lanes than Equation (9). Therefore, the energy value of Equation (8) is larger than Equation (9) and the following relationship holds:A to F have the following order of magnitude:Substituting the result of Equation (10) into Equation (7), the energy values at each point from A to F are shown in the energy versus time graph at the bottom of B to F using the time taken to travel between the points B and F and the speed information of the vehicle can be estimated as follows:B and F, respectively, and x = 0 is assumed, but the radar position changes to Based on Equation (11), the energy values detected at each point as the radar moves from Next, the range of the values of the parameters mentioned in In order to verify the method proposed above, metal lanes and radars were installed, and field tests were performed as shown in To test the lane detection method, four scenarios were established by varying the installation of metal lanes and vehicle movement path as shown in The next step was to determine the threshold value to distinguish lanes and roads by the energy detector output value. For this purpose, energy detector output values were collected through experiments with and without metal lanes. The histogram was plotted by measuring approximately 6000 energy detector output values at different locations between the vehicle and the radar while the vehicle was in the lane. The following are the experimental results for each scenario. The energy detector output for Scenario 1 and the IR-UWB signal at 3.9 s are shown in The energy detector output for Scenario 2 and the IR-UWB signal at 1.6 s at the maximum energy in metal lane 1 are shown in The travel time, speed, and estimated metal lane spacing among maximum energy value points for each metal lane are shown in Scenario 4 is when a vehicle moves from metal lane 4 to 5 and goes over into the lane on the left. In Finally, the reflection signal by the manhole that could be mistaken as a metal lane among the metallic facilities on the road was examined. The round and square manholes were tested, and the manholes used for the measurement are shown in An IR-UWB radar-based lane detection method was proposed and verified through experiments. Metal lane markers were installed because radar cannot be used to recognize common paint lane markers. The proposed method estimates lane spacing using the periodic changes in reflected energy values in the regularly installed lane and by comparing it with the actual value to determine a lane. This result can be used in conjunction with the LDWS to assist drivers in an environment where camera-based lane recognition technology does not operate smoothly or to improve the autonomous driving recognition technology. In addition, the proposed lane recognition system can also be utilized for estimating the travel distance or position through counting of lane markers. The results from field experiments showed that the obtained lane detection rates were approximately 86%–94% for the experimental scenarios and 90.9%–98.7% in the sample collection step for the histogram. This difference was because the experiment was performed by precisely moving the vehicle at a speed of 10 km/h in the sample collection step, whereas the vehicle moved at 20–30 km/h in the experimental scenarios and slightly swayed toward the left and right. This difference may also be attributed to the difference in the number of samples. The lane spacing estimation error was in the range of 22–38 cm on average; however, actual errors occurred up to 97 cm. The reason for the large error in the lane spacing estimation was that the vehicle did not move in a direction that was completely parallel to the lane. However, this type of vehicle swaying is encountered at all times, even during actual vehicle driving scenarios. This error can be compensated for if the inertial sensor information or the steering information of the vehicle can be used. Accurate lane spacing estimates will help eliminate the sources of high reflectivity such as manholes.In this study, the possibility of lane detection using IR-UWB radar was demonstrated. Although this method is difficult to apply to all roads owing to the installation cost of metal lanes, it can be applied at places where cameras encounter difficulty while operating such as tunnel entrances and exits, places that are prone to fog, and places with direct sunlight. As radars must also be installed, our proposed model may be appropriate for vehicles requiring high safety, such as public transportation, rather than for all vehicles. The areas for further study toward commercialization are as follows. First, the energy detector output must be modeled by accumulating and analyzing experimental data in various road environments such as curved roads and sloped roads. To increase the lane detection rate, research on lane detection-specific IR-UWB and antenna radiation pattern optimization is also required.


A continuum damage model is proposed to predict the intralaminar progressive failure of CFRP laminates based on the modified Puck’s theory. Puck’s failure criteria, with consideration of the in situ strength effect, are employed to evaluate the onset of intralaminar failure including fiber fracture and inter-fiber fracture. After damage initiation, a bilinear constitutive relation is used to describe the damage evolution process. In strict accordance with Puck’s concept of action plane, the extent of damage is quantified by the damage variables defined in the fracture plane coordinate system, rather than the traditional material principal coordinate system. Theoretical and experimental evaluation of CFRP laminates under different loading conditions demonstrates the rationality and effectiveness of the proposed numerical model. The model has been successfully implemented in a finite element (FE) software to simulate the intralaminar progressive failure process of CFRP laminates. A good agreement between the experimental and numerical results demonstrates that the present model is capable of predicting the intralaminar failure of CFRP laminates. Carbon fiber reinforced polymers (CFRPs) are being increasingly used in industry due to their advantageous properties such as high specific strength and stiffness, good resistance to fatigue and corrosion, as well as flexibility in design. CFRP laminates are now widely applied in various fields, including aerospace structures, windmill blades, and pressure vessels. Nevertheless, the design of CFRP composite structures is still rather conservative in engineering practice. A large quantity of time-consuming and expensive tests must be carried out to ensure structure safety. To efficiently reduce the time and cost as well as fully exploit the advantages of CFRPs, there is an imperative need for the accurate theoretical prediction of the failure of CFRP laminates. However, the failure mechanisms of CFRP laminates are very complex due to their inherent anisotropy and the variety of failure modes. Hence, developing a reliable failure theory for CFRP laminates is a very challenging task.The failure process of CFRP laminates can be divided into two stages. First the damage initiates in a ply, and then it gradually propagates through the laminate until the structure reaches the ultimate failure load . The conA large number of failure criteria have been developed to predict the damage onset of CFRP laminates. Classical criteria such as the maximum stress or strain, Hoffman, and Tsai–Wu fail to distinguish the intralaminar failure modes, namely the matrix failure and the fiber failure. In 1980, Hashin proposed a set of criteria which separate the fiber and matrix failure modes ,11, theyDespite its good performance for unidirectional laminae, Puck’s theory predicts an initial failure stress of laminates that is significantly lower than experimental results . The undl-n-t). According to Puck’s failure theory, inter-fiber fracture is exclusively determined by the stresses acting on the fracture plane  loading , while t loading . A sketcσ = F/Lwt, where w and Lt are the width and thickness of the specimen. The axial average stress–strain curves are shown and compared in For the laminate under uniaxial tensile loading, a total of 110,784 elements were used in the model. The axial average stress is defined as the external load per unit cross-sectional area: F–Δ curve obtained from the experimental data is plotted in F is the external load measured in the test, and Δ is the relative displacement. As shown in For the laminate under uniaxial compressive loading, a total of 38,892 elements were used in the model. The In the present study, a continuum damage model based on the modified Puck’s theory is developed to simulate the intralaminar progressive failure of CFRP laminates. The in situ strength effect and the nonlinear shear behavior of CFRPs are considered in the model. The modified Puck’s failure criteria are adopted to determine damage initiation, while a bilinear constitutive relation is used to describe damage evolution. In strict accordance with Puck’s concept of action plane, the equivalent stress/strain and the damage variables are defined in the fracture plane coordinate system rather than the traditional material principal coordinate system. Theoretical and experimental evaluation of CFRP laminates validates the rationality and effectiveness of the proposed model. The numerical model has been implemented in an FE software to simulate the progressive failure of CFRP laminates, and good correlation between the numerical and experimental results is observed. Future research will combine the proposed model with the interface fracture modeling techniques to simulate both intralaminar and interlaminar damage of CFRP laminates.


The solid stress (SSg) that develops inside a cancer is an important marker of cancer’s growth, invasion and metastasis. Currently, there are no non-invasive methods to image SSg inside tumors. In this paper, we develop a new, non-invasive and cost-effective imaging method to assess SSg inside tumors that uses ultrasound poroelastography. Center to the proposed method is a novel analytical model, which demonstrates that SSg and the compression-induced stress (SSc) that generates inside the cancer in a poroelastography experiment have the same spatial distribution. To show the clinical feasibility of the proposed technique, we imaged and analyzed the normalized SSg inside treated and untreated human breast cancers in a small animal model. Given the clinical significance of assessing SSg in cancers and the advantages of the proposed ultrasonic methods, our technique could have a great impact on cancer diagnosis, prognosis and treatment methods. We present a new, non-invasive and cost-effective imaging method to assess solid stress inside tumors using ultrasound poroelastography. To show the clinical feasibility of the proposed technique, we imaged and analyzed the normalized solid stress inside treated and untreated human breast cancers in a small animal model. Given the clinical significance of assessing solid stress in cancers and the advantages of the proposed ultrasonic methods, our technique can have a great impact on cancer diagnosis, prognosis and treatment. I.The mechanical microenvironment plays an important role in the growth, invasion and metastasis of cancers There are three main sources of SSg inside cancers: external stress, swelling stress and growth-induced or residual stress. The external stress is created by the resistance of the normal tissue to newly grown cells in cancers, which try to expand against the surrounding normal tissue. The surrounding tissue resists this expansion by exerting an opposite stress. Swelling stress is caused by chemical expansion as the interstitial space of the cancer may have a high concentration of negatively charged hyaluronan chains, and the repulsive electrostatic force among these negative charges can cause swelling of the tumor. The residual stress can be defined as the remaining stress inside a body, when all the external loads on the body have been removed Assessment of SSg inside tumors is of great clinical significance for various reasons. By compressing the blood vessels inside the tumor, SSg can cause deficiency of oxygen supply in the cancer, also known as hypoxia. Hypoxia is responsible for impaired perfusion and can reduce the killing potential of the immune cells et al.et al.et al.et al.A number of invasive techniques have been proposed for estimating SSg inside cancers. In the works of Stylianopoulos Ultrasound elastography (USE) is a non-invasive, safe and cost-effective imaging modality that is used to assess the strains generated in the tissue by the application of a small external compression In a recent work from our group II.A.1)Our analytical model for radial and circumferential SSc inside the tumor is based on the following assumptions: 1) the tumor and normal tissues behave as poroelastic materials, and biphasic theories can be applied to describe their behavior; 2) the tumor is spherical in shape; 3) the tumor is perfectly bonded to the normal tissues; 4) the spatial distribution of the mechanical properties inside the tumor is uniform; 5) the assumption of ‘remote load’ is satisfied inside the tumor, i.e., the tumor is much smaller in comparison to the sample 2)The proposed analytical model for SSg inside cancers is based on a spherical model of the tumor as shown in The equation for the compression-induced fluid pressure (FPc) inside a spherical tumor in a poroelastography experiment at a time The relationship between the radial/circumferential SSc and FPc can be written as In B.Twelve mice  implanted with triple negative breast cancer (TNBC) were scanned once a week for three subsequent weeks. A mouse model of human TNBC was used for these experiments. TNBC patient derived xenograft (PDX) tumors was established by placing small pieces of freshly collected TNBC human cancer xenografts (BCM-4913) derived from primary human TNBC in the fat pad of immunocompromised female NOD/SCID gamma (NSG) mice The samples were scanned using a 38-mm real-time Sonix RP linear-array scanner  that has 128 elements, a bandwidth between 5 and 14 MHz, a center frequency of 6.6 MHz, 50% fractional bandwidth at −6 dB, sampling frequency of 40 MHz, and 1 mm beamwidth at the focus. A force sensor (Tekscan FlexiForce) was placed between the top surface of the gel pad and the compressor plate to record the applied force during compression. In all our poroelastography experiments, creep compression was performed in the region of interest in the animals. In a creep compression protocol, a constant pressure is applied on the sample. In our experiments, we applied a uniaxial pressure of 1–4 kPa for one minute To compute the elastograms from the pre- and post-compressed RF data in simulations and experiments, we used the method described in The axial and lateral strains at a specific time point were calculated in a cumulative manner To determine the value of III.Analytical Model:The behavior of the radial and circumferential SSg as a function of In et al.In These results demonstrate that our proposed analytical model is able to model SSg in different scenarios of clinical interest for the analysis of tumors, i.e., change in growth strain, time increment etc. Our results match well with those previously reported in the literature using finite element simulations A.B-mode images and corresponding reconstructed SSn distributions obtained from data acquired from two untreated mice at three different time points  are shown in B-mode images and corresponding reconstructed SSn distributions obtained from data acquired from two treated mice at three different time points  are shown in The mean value of IV.In this paper, we developed a method for imaging the normalized SSg inside tumors. The proposed methodology is based on an analytical model of SSg distribution inside the tumor that connects the SSg with Distribution of SSg in cancers is clinically informative as it directly affects cancer’s growth and metastasis while modulating the cancer microenvironment. SSg compresses the blood vessels and causes reduction in outflow of the fluid thus increasing IFP. Vessel compression also reduces the flow of the immune cells inside the tumor, induces hypoxia and acidity, which decreases the access of drugs to the tumor The described method to assess the stress distribution inside tumors requires knowledge of the parameter The protocol used in our poroelastography experiments is creep compression. The proven relationship between the actual solid stress and the stress developed in a poroelastography experiment is only true when the creep compression protocol is used and the assumptions mentioned in In poroelastography experiments, we used conventional linear array imaging for data acquisition for the following reasons. Firstly, although other advanced methods such as compound plane wave imaging have higher frame rate, they have lower spatial resolution In our poroelastography experiments, we used one minute long data acquisitions. This data acquisition duration might be an issue in patient imaging as the breathing and motion of the patient and sonographer may introduce decorrelation noise in the data In the present form, our work allows estimation of the normalized SSg but does not allow quantification of the actual SSg. However, it is important to note that, in many applications, such as drug delivery and/or diagnosis and prognosis of cancers, the spatial distribution of SSn and the relative change in the value of SSg obtained from the temporal distribution of V.In this paper, we have developed a non-invasive, poroelasto-graphy-based method to image the normalized solid stress inside tumors in vivo. The proposed method is based on an analytical model of the solid stress distribution, which demonstrates that the solid stress inside the tumor has the same spatial distribution as the compression-induced stress generated in the tumor during a creep compression experiment. As the solid stress is an important component of the cancer microenvironment, the proposed technique may provide new information about cancer mechanopathology and, eventually, lead to improved cancer diagnosis and treatment methods.


In recent years, the measurement of dam displacements has benefited from a great improvement of existing technology, which has allowed a higher degree of automation. This has led to data collection with an improved temporal and spatial resolution. Robotic total stations and GNSS  techniques, often in an integrated manner, may provide efficient solutions for measuring 3D displacements on precise locations on the outer surfaces of dams. On the other hand, remote-sensing techniques, such as terrestrial laser scanning, ground-based SAR (synthetic aperture radar) and satellite differential interferometric SAR offer the chance to extend the observed region to a large portion of a structure and its surrounding areas, integrating the information that is usually provided in a limited number of in-situ control points. The design and implementation of integrated monitoring systems have been revealed as a strategic solution to analyze different situations in a spatial and temporal context. Research devoted to the optimization of data processing tools has evolved with the aim of improving the accuracy and reliability of the measured deformations. The analysis of the observed data for the interpretation and prediction of dam deformations under external loads has been largely investigated on the basis of purely statistical or deterministic methods. The latter may integrate observation from geodetic, remote-sensing and geotechnical/structural sensors with mechanical models of the dam structure. In this paper, a review of the available technologies for dam deformation monitoring is provided, including those sensors that are already applied in routinary operations and some experimental solutions. The aim was to support people who are working in this field to have a complete view of existing solutions, as well as to understand future directions and trends. Monitoring the health of dam infrastructures has a key role in ensuring their safety conditions and maintaining their operational functions. Dam failures represent a high-risk for people, human settlements, infrastructures, and the environment. As a consequence, careful surveillance with the aim of detecting any possible critical situations is required. In addition, when the failure status is not completely reached but the operational conditions of a barrage cannot be fully guaranteed, a severe economic loss may result from to the interruption of energy production or other related activities such as hydraulic regulation and water storage.The complexity of dams calls for the use of multiple sensors for monitoring. Each sensor focuses on a different area of the main barrage, the slopes surrounding the water reservoir, and the utility structures. In addition, different processes  have to be measured using a suitable data acquisition rate that should be comparable to the velocity of the observed ongoing processes. Monitoring has not only the purpose of pre-alerting a forthcoming collapse but may provide useful information to verify the design parameters, to investigate the causative reasons of deformation processes, and to learn lessons to be implemented in future projects .Measuring structural deformations of dams aims to detect rigid and non-rigid changes of the geometric shape of the structure, at both local and general level . During Until the 1950s, the static monitoring of dams was mainly based on geodetic control networks ,11 to meIn the 1960s the introduction of automatic data acquisition and telemetric transmission allowed for the collection of data at a higher rate, up to continuous monitoring. These solutions provided long-term data series that improved the capability of analyzing deformation patterns. Over the years, technological developments have continuously increased the precision, the degree of automation, the data handling capability of the adopted geodetic and geotechnical sensor technology. In parallel, during the last decades, dam monitoring has benefited from the development of remote-sensing techniques from ground-based and satellite platforms. These have offered unprecedented opportunities for improving the structural analysis, since they extended the monitoring to a large portion of a structure, instead of a limited number of few CPs . Among tMethods based on Global Navigation Satellite Systems (GNSS) have been widely applied for the measurement of the dam’s displacements and in the nearby areas. Initially, GNSS networks were adopted for periodic measurements of CPs, controlled by a set of reference points established in proximal stable areas. In the recent years, automatic systems adopting differential GNSS sensors, able to work in continuous mode, have been developed to be integrated into early-warning systems for the safe maintenance of the dam ,20. RealSince there is not any sensor capable of recording the full information needed for monitoring a dam, great attention has been concentrated on the development of integrated monitoring systems (IMS), see Chrzanowski . MoreoveThis paper provides an overview of existing and innovative geodetic and remote-sensing methods for dam deformation monitoring. A description of the characteristics of deformations that can be observed on a dam is given in Dams are generally classified as earth-filled , concretThe external inputs that may alter the geometry of a dam can be ordinary, including thermal forces due to the air temperature and solar warming , and hydTraditionally, two different types of absolute and relative displacements may be observed on a dam: horizontal and vertical displacements. On the other hand, Chrzanowski  remarks Vertical displacements may be observed on the dam upper crown, in the internal inspection tunnels, in the foundations, and at the interface with the bedrock on the lateral flanks of the valley. Vertical displacements may indicate an overall settlement of the structure if observed with respect to the external area or rotational trends in the case of differential height variation between two points. The need of carefully monitoring the interface between the dam body and the rock boundary is quite important to highlight criticisms linked to relative sinking and shifting, which may be preliminary events to major failures.Chrzanowski  discusseBesides measuring displacements, there are two other relevant aspects in dam monitoring: the conditions of the outer surface of the structural elements and the natural and anthropogenic processes in the surroundings. The alteration of those materials used for preserving the inner strata may lead to some damage of the structural components and may open the way to water infiltration. Therefore, cracks and fractures have to be mapped and monitored to measure extensions and enlargements. Land subsidence (sometimes correlated to the variation of the water level in the basin), slope and rock failures, pore water pressure, water pumping and water infiltration may have an indirect impact on the structural and operational conditions of the dam itself.A consolidated technique for monitoring horizontal displacements in large dams is based on optical collimators . They alAutomatic collimators based on opto-electronic technology have been developed for continuous dam monitoring and are in operation at several dams. Using such type of sensors, a sub-millimeter accuracy may be reached but they still suffer from local changes of the atmospheric refractive index . A referGeodetic triangulation networks  and optical leveling networks  have been the most common approaches adopted for static monitoring of dam displacements in the last century. In the case of geodetic triangulation networks, CPs are usually located on concrete pillars on the dam crest and on stable areas outside the structure to be used as reference points. In correspondence of these locations, theodolites and targets can be set up by using forced centering to eliminate centering errors. An example of such a kind of geodetic networks has been reported by Guler . In the last decades, new geodetic sensors have been developed and introduced for routine use in the geodetic monitoring of dams. In particular, robotic total stations (RTS), incorporating a high-precision rangefinder are used for the direct measurement of 3D coordinates of reflectors adopted as CPs. In modern instruments, an internal camera allows for image-based techniques to be exploited for target recognition and precise measurement ,34, whicOptical leveling is still widely applied for monitoring vertical displacements of large infrastructure ,37, inclIn earthen structures where the expected vertical displacements may be larger than in concrete dams, trigonometric leveling has been applied , obtainiHydrostatic leveling  is a potAlternative solutions for detecting vertical displacements, adopting image processing techniques, have been proposed in the literature , but theThe use of Global Navigation Satellite System (GNSS) techniques  for defoIn order to achieve the highest accuracy, a special attention has to be devoted to the design of the monitoring network. One or more reference stations should be included and regularly controlled using external links in order to determine if movements have occurred. Some statistical techniques have been developed to help with this analysis, see For real-time positioning methods, high acquisition rates (up to 1 s or less) and accurate satellite orbits, as well as clock corrections, are needed. In real-time, GNSS antennas deployed on the dam crest may be dealt with as kinematic rovers relative to the nearby master stations (within a range from 0.1 km to 2 km).Data processing provides an estimate of the 3D components of vectors between the reference and each CPs (baseline) per each epoch. By analyzing the baseline time series, the deformation pattern may be derived. The reliability of the analysis strongly depends on a proper design of the GNSS control network that should include redundant connections to implement a robust deformation analysis based on a Least-squares adjustment and statistical data analysis and testing . The anaOne of the most recent and complete studies carried out on dam monitoring by GNSS is the work by Montillet  that conThe potential for an automatic and continuous GNSS monitoring system for dam structural deformation measurement has been already explored in 1989 by De Loach . He propRutledge  marked aSeveral works directly compared deformations obtained from GNSS to deformations obtained with other sensors: coordinatometer ; inverteIn these papers, some problems related to the different reference systems of the various devices were not explicitly addressed. This is probably due to the fact that data gathered by different sensors have never been directly integrated. Dardanelli  presenteThe implementation of new sensors may need the integration of multiple observations requiring a reformulation of the functional model of geodetic/GNSS network adjustment .An interesting innovative approach for the measurement of 3D displacements on specific CPs is offered by terrestrial-based radio frequency ranging technology. This technique relies on a measurement principle that is similar to that of GNSS but based on data broadcasted from ground-based units rather than from satellites. A centimeter-level accuracy for static positioning using a carrier-phase measurement may be obtained for monitoring the structural movement in many applications. For example, the “Locata” system consists of a network (LocataNet) of time-synchronized pseudolite-like transceivers (LocataLites), which can be deployed around a structure to obtain an optimal network geometry despite of the site constraints. In Choudhury and Rizos , the firADM techniques  offer thFor each survey, the geometry of the dam surface, including possibly deteriorated or damaged portions, may be extracted and represented by raster or vector maps. Similarly, the comparison of repeated surveys provides deformation maps or a set of displacement vectors that describe the structural modifications. The ADM techniques that have been experimentally tested on dams include TLS, GBSAR and satellite D-InSAR. Close-range photogrammetry  has beenTerrestrial laser scanning (TLS) can directly provide high-density 3D data and additional information, such as intensity and RGB colors ,73. AlthSeveral systematic error components may contribute to the total error budget of TLS, which are likely to degrade the accuracy of the measurements. In the test field established on the Cancano Dam  to measure the real performance of TLS for dam monitoring applications , the negSeveral studies have been published on the inner calibration of specific TLS instruments or categories of instruments . Different models for correcting inner systematic errors have been summarized in the literature . The infAnother important aspect that may result in systematic errors is the registration of multiple point clouds. This task is required to merge more laser scans collected from different standpoints or to co-register point clouds collected at different epochs. In TLS practice, rigid-body transformations are typically applied for registration/georeferencing, since the correct scaling is assumed. In general, corresponding points for registration are defined using targets, whose coordinates may be also independently measured by geodetic techniques to establish a topographic reference system. Very often, retro-reflective targets are adopted to help automatic recognition in scans. In Alba , the resModeled TLS data may provide an accuracy higher than the single point precision . DiffereAlternatively, the whole point cloud describing the dam surface may be segmented into several subsets, each of them to be approximated by using simple shapes (piecewise surface models). Planes ,78 and rGround-based synthetic aperture radar (GBSAR ) is a raIn the literature, two different types of acquisition modes are described: the continuous and discontinuous modes. In the case of the continuous mode, the GBSAR is permanently installed in front of a given structure, acquiring data periodically. The acquisition period can be as short as a few minutes, or a few seconds, depending on the characteristics of the adopted radar instrument. This configuration is suitable to carry out near real-time deformation monitoring, while it offers the best performances in terms of measurement density, precision and robustness . Examplecoherence of the measurements. In the case of dam monitoring the coherence is usually high; however, it is higher in the continuous mode than in the discontinuous one. For this reason, the best measurement performance is achieved in the continuous mode. A fifth advantage is that the GBSAR monitoring provides a high temporal resolution: image acquisition can be operated in matters of a few minutes, if not a few seconds [GBSAR-based deformation monitoring offers interesting characteristics that make this solution complementary to other techniques. The first advantage is related to the remote-sensing nature of GBSAR, which can be accomplished without installing sensors or targets on the structure at hands, while operating at a significant distance from it (up to 1–2 km). This can be useful to guarantee the safety of the monitoring activities, especially in the case of emergency situations . The sec seconds . This prThe most important limitations of GBSAR are briefly described in the following. First of all, data coherence is a condition sine qua non to carry out monitoring, as already discussed. The second limitation concerns the ambiguous nature of the GBSAR deformation measurements because they also require the estimation of the phase ambiguity. This operation is usually straightforward when using continuous-mode data, while it can be critical when using the discontinuous measurements . AnotherA number of experimental GBSAR monitoring results show the potential for dam deformation monitoring. However, it is worth noting that an operational GBSAR dam monitoring system, for instance, based on a permanent installation, has not been documented yet in the literature. This is probably due to different causes, among which is the high cost of the instrumentation.Real-aperture radar interferometric sensors may represent an alternative to GBSAR . HoweverSpaceborne DInSAR was initially applied to the analysis of ground subsidence over large areas or to detect earthquake-induced deformations . Thanks Among the A-DInSAR techniques , PersistThe application of A-DInSAR was used to detect surface displacements of an earth-filled dam at La Pedrera Reservoir . The opAnghel  applied The validation of A-DInSAR has received a lot of attention in the last two decades . In addiThe results obtained so far are quite encouraging for promoting future efforts in the application of spaceborne SAR data for dam deformation measurement. Indeed, the availability of last-generation very high-resolution images acquired by TerraSAR-X and Cosmo-SkyMed constellations may allow us to obtain better ground resolution and shorter revisiting-time by means of algorithms that may produce increasingly reliable results, see Osmanoğlu .Due to the presence of several processes that might affect the dam stability and because of the size of such structures, monitoring is often quite complex and may require an integrated monitoring system (IMS ). While www.goca.info) developed at Hochschule Karlsruhe , which integrates GNSS, theodolites and other sensors on the hardware side, along with models for data analysis and prediction. The GOCA system can be used for online control and early-warning. A few software packages may be used to integrate observations from multiple permanent geodetic sensors. For example, the ALERT system developed at the Canadian Centre for Geodetic Engineering [Examples of IMSs applied to dam monitoring are difficult to find in the literature. This is mainly motivated by the fact these applications have not been given too much attention by the scientific community, though they are really important in the daily practice of those organizations dealing with dam administration and management. An interesting example is the system GOCA . This cTime series of displacements derived from geodetic and remote-sensing observations as well as geotechnical data collected on dams have to be analyzed in order to find the relationships with loads. These are mainly the water level in the reservoir and the external temperature. Once these relationships have been identified, from the knowledge of loads, short- (a few months) and long-term (one year) forecasting of dam deformations may be carried out. The complexity of this analysis depends on several factors: the type of dam, the specific phase of its lifetime , the age of the structure, the presence of structural or deterioration problems. In addition, each causative reason may feature different patterns: harmonic fluctuations, locally linear trends, irregular patterns. As a result, investigating the dependency of displacements upon loads may be quite difficult. Standard statistical analysis and filtering techniques may not be sufficient to capture deformation trends excluding seasonal effects. In order to improve this task, some tailored methods have been developed and experimentally tested. These methods could be classified as statistical methods see  and deteThe statistical methods try to establish a relationship between forcing actions and the resulting deformations measured on the dam without considering the mechanical aspects. This type of analysis may provide an important contribution to dam deformation analysis and interpretation when long time-series are available. Statistical methods can also precede the application of deterministic methods in a cascaded processing workflow.Multi-regression models (MRT) have a long tradition in the analysis of dam deformations, as reviewed in Zou . HoweverDai  proposedYigit  applied Pytharouli and Stiros  considerThe deterministic methods compare displacements and geotechnical measurements that have been observed on a dam to the corresponding parameters obtained from numerical modeling of the structural behavior under external loads . This inDeterministic models of expected deformations may be used for the design of a new monitoring scheme or for the improvement of existing ones. Szostak-Chrzanowski  presenteChen  developeGikas and Sakellariou  analyzedA further step forward in this research direction was made by Corsetti , who recWhile several papers have been applied to demonstrate how well the real dam have followed the design conditions, the progress of research seems to go in the direction of combining observations and numerical modeling. This solution may be useful to achieve a better calibration of theoretical numerical models according to the real observed conditions, offering the chance to carry out more precise and timely forecast of possible critical conditions.This paper has reported a review of modern geodetic, GNSS and remote-sensing techniques that may be applied for monitoring dam deformations, together with geotechnical and structural sensors. While geodetic techniques have a long tradition and may benefit today from the up-to-date instrument technology and degree-of-automation, the other methods represent the real novelty and potentially open unprecedented perspectives. For this reason, a thorough analysis has been done of the so-called areal deformation measurement (ADM) techniques, including ground-based  and spaceborne (DInSAR) sensors. Since ADM techniques allow the extension of the investigated area beyond the limited locations defined by control points. GNSS-based methods may offer now a lower dependency on the local topographic constraints , provided that there is sky visibility. The general picture offered by these new technologies is promising, even though future efforts should be put to understand which techniques have the potential to follow-up in the regular practice of dam monitoring and surveillance and which may only offer a contribution to scientific investigations. Attention should be also given to other emerging technologies, such as synthetic aperture LADAR . The increasing use of satellite Earth observations (EO) is an important point to discuss. On one side, such data may be used for the remote monitoring of dams and the nearby environment, whose influence on the safety of the barrage itself may be really relevant. On the other side, the growing availability of new improved data sets  is supposed to foster even more the application of satellite EO data.Attention should be also paid to the integration of data coming from different types of sensors that may offer a different prospect of the same construction. In particular, geodetic measurements can provide surface horizontal/vertical displacements of control points located in key positions, remote-sensing techniques may output a broader picture of displacements over the full structure and the surrounding, while geotechnical/structural sensors may yield important information of those processes inside the dam structure and the foundations. Such a data/sensor integration may create added value and increase data redundancy to be used for cross-checking observations.


With increasingly prevalent wireless sensors and devices, low power and lossy networks (LLNs) play an essential role in the realization of ubiquitous computing and communication infrastructure, which, in turn, leads to enhanced data accessibility and availability. A multicast protocol for LLNs (MPL), has been standardized to provide both efficient and reliable multicast communication. Due to the shared wireless medium, lack of tamper resistance, and inherent resource constraints, MPL-based LLNs are undoubtedly vulnerable to various Denial-of-Service (DoS) attacks. In this paper, we propose a heuristic-based detection scheme, called HED, against the suppression attack in MPL-based LLNs, where a malicious node multicasts a series of spoof data messages with continuous sequence numbers to prevent normal nodes from accepting valid data messages and cause them to delete cached data messages. In the HED, each node maintains an increment rate of the minimum sequence number in the Seed Set to detect the potential malicious node by comparing the recent increment of sequence numbers with the heuristically calculated increment threshold of sequence numbers. We evaluate the proposed scheme through extensive simulation experiments using OMNeT++ and compare its performance with original MPL with and without adversary, respectively. The simulation results show high detection rate and packet reception rate but low false detection rate, and indicate that the proposed scheme is a potentially viable approach against the suppression attack in MPL-based LLNs. A rapidly growing number of wireless sensors and devices (later nodes), and hybrid networks are leading the emergence of Internet-of-Things (IoT) and its applications, where a myriad of multiscale nodes are seamlessly blended and communicate with each other . It has As a major part of IoT, low power and lossy networks (LLNs) play an essential role in the realization of ubiquitous computing and communication, where a set of resource-constrained nodes in terms of communication, computation, memory, and energy communicates among themselves directly or indirectly via lossy links. With the increasing demand of sharing information and knowledge and coordinating decisions, the Internet Engineering Task Force (IETF) Working Group has proposed a multicast protocol for LLNs, also referred to as MPL , as the We significantly extend our previous work , and anaWe propose a heuristic-based detection scheme, called HED, to efficiently mitigate the suppression attack in MPL-based LLNs. In the HED, each node maintains an increment rate of the minimum sequence number in the Seed Set, and compares the recent increment of sequence numbers within a time period with the heuristically calculated increment threshold of sequence numbers to detect potential malicious node.We propose a simple analytical model of the HED and show its numerical result in terms of miss detection rate. We also revisit and implement the original MPL with and without adversary for performance comparison. In addition, the original MPL without adversary will be used as the upper bound of packet reception rate.In light of the above, we investigate a suppression attack and propose a heuristic-based detection scheme, called HED, to efficiently mitigate the suppression attack in MPL-based LLNs. In the suppression attack, a malicious node multicasts a series of spoof data messages with continuous sequence numbers to prevent legitimate nodes from accepting valid data messages, and cause them to delete their cached data messages as well. Although the countering of jamming attacks and its variants have been extensively studied , the supWe develop a customized discrete event-driven simulation framework by using OMNeT++  and evalThe remainder of the paper is organized as follows. Prior approaches are presented and analyzed in In this section, we categorize and analyze a variety of existing attacks and countermeasures in terms of wireless ad hoc networks, low power and lossy networks, and Internet of Things.In , a camouIn , a DSR-bOver the last few years, researchers have explicitly studied the numerous security issues associated with LLNs. In the VeRA , a versiThe SVELTE  proposesIn summary, various attacks and their countermeasures have been well studied throughout various networks and environments. However, little attention has been shown to the suppression attack in the realm of MPL-based LLNs.In this section, we begin with an overview of the multicast protocol for low power and lossy networks. Then, we analyze the suppression attack with a preliminary result. Finally, we present both system and adversary models and propose a heuristic-based detection scheme, also called HED, against the suppression attack in MPL-based LLNs.Multicast protocol for low power and lossy networks, also referred to as MPL , is a IPWhen a source node has a data message to send within an MPL domain, it generates a message that includes the MPL domain address as a destination address. Here, the MPL domain is a scope zone in which nodes subscribe to the same MPL domain address and also participate in the dissemination of MPL data and control messages. The source node also piggybacks its identifier, a newly generated sequence number, and the payload in the data message. It then schedules a multicast of data message using the Trickle Algorithm, which is completed without any prior indication that the neighboring nodes have received the data message. After transmitting the data message a limited number of times, the source node terminates the transmission process of data message.When the node that subscribes to the same MPL domain address has received the data message, it extracts the source node identifier and sequence number to determine whether or not the data message has been received. If the sequence number is less than the minimum sequence number maintained in the Seed Set, or equal to the sequence number stored in the Buffered Message Set, the receiving node discards the data message because it believes that it has received the data message before. In the MPL, a Seed Set records a sliding window that is used to determine the sequence number of data message that the node is willing to receive. The Seed Set consists of three components: the identifier of source node, the minimum sequence number that the node is willing to receive, and the lifetime of the Seed Set entry. Additionally, a Buffered Message Set records recently received data messages that have a sequence number greater than the minimum sequence number in the Seed Set. The Buffered Message Set is composed of three components: the identifier of source node, the sequence number of data message, and the payload of data message. If the sequence number is equal to the minimum sequence number in the Seed Set, the receiving node updates the minimum sequence number to one greater than the received data message’s sequence number. At this point, it deletes any data message that has a sequence number less than the updated minimum sequence number from the Buffered Message Set. If the sequence number is greater than the minimum sequence number in the Seed Set, but not stored in the Buffered Message Set, the receiving node adds the received data message into the Buffered Message Set. Then, the receiving node multicasts the received data message using the Trickle Algorithm to all neighbor nodes that subscribe to the same MPL domain. Here, an overall information flow of normal node that receives a data message is shown in Nodes that subscribe to the same MPL domain also periodically exchange a MPL control message using the Trickle Algorithm to discover new data messages that have not been received, where MPL control message contains the information of Seed Set and Buffered Message Set. If a node discovers a neighbor node that has not received certain data messages, it multicasts those data messages using the Trickle Algorithm.The MPL uses a sequence number to normally maintain the order of data messages transmitted from a source node. However, the sequence number can be misused by an adversary to attack the network. For example, a malicious node can intentionally multicast a series of spoof data messages with continuous sequence numbers within a short period of time to increase the minimum sequence number stored in the Seed Set. This can prevent the legitimate nodes from accepting valid data messages with a sequence number less than the minimum sequence number from the source node, and cause them to delete data messages with a sequence number less than the minimum sequence number from the Buffered Message Set.seq) to a node , and reprogram it to behave maliciously [iciously . Howevericiously , where aiciously . In thisMajor Operations: The basic idea of HED is that each node maintains an increment rate of the minimum sequence number in the Seed Set, and compares the recent increment of sequence numbers within a time period with the heuristically calculated increment threshold of sequence numbers to detect the potential malicious node in MPL-based LLNs. The HED has three major operations. First, each node records a trace of multicast operations of neighbor nodes executed during an observation window (MT) to monitor their multicast operations. We deploy an observation window (nid), sequence number of the first received data message within observation window (fs), timestamp of the first received data message within observation window (ls), and timestamp of the last received data message within observation window  and introduce an additional component: increment rate of the minimum sequence number within observation window. Thus, the Seed Set SS consists of four components: identifier of source node (nid), minimum sequence number that the node is willing to receive : Second, the packet reception rate (PRR) is measured against suppression attack rate, number of malicious nodes, and simulation time in As shown in False Detection Rate: Third, the false detection rate is measured by varying suppression attack rate, number of malicious nodes, and Changes of Increment Rate: Finally, we measure the changes of the increment rate without and with adversary against simulation time and a filter gain constant In this section, we first analyze and compare the suppression attack with well-known jamming attack in terms of attack method, stealthiness, attack energy efficiency, and level of denial of service. Then, we further explore design issues and extensions of HED for future research.The basic idea of suppression attack is that a malicious node multicasts a series of spoof data messages with continuous sequence number to increase the minimum sequence number stored in the Seed Set, which can prevent the legitimate nodes from accepting valid data messages and cause them to delete the cached data messages. For jamming attack, a malicious node needs to continually transmit a radio signal to block any legitimate access to the medium and interfere with reception. Compared to the jamming attack, the suppression attack is much stealthier. This is because the malicious node acts as a normal node but multicasts a limited number of data messages to legitimate nodes to increase the minimum sequence number stored in the Seed Set, which can cause the legitimate nodes to reject valid data messages by themselves. In addition, the suppression attack has lower energy consumption compared to that of jamming attack because the less number of attack packets  are generated and multicasted by malicious node in the suppression attack. However, the jamming attack has to continually broadcast a radio signal, consuming more energy. The suppression attack makes all one-hop neighbor nodes reject valid data messages and delete the cached data messages. Thus, the valid data messages cannot be transmitted and shared further in the network. Eventually, the suppression attack can lead to an extremely severe denial of service in MPL-based LLNs.In the HED, each node individually monitors the malicious node to detect the potential multicasting misbehaviors. Similar passive monitoring-based approaches are also found in ,42. SincIn this paper, we present and analyze the suppression attack with a preliminary result in MPL-based LLNs, where a malicious node multicasts a series of spoof data messages with continuous sequence numbers to prevent the normal nodes from accepting valid data messages and cause them to delete the cached data messages. To resolve this issue, we propose a heuristic-based detection scheme to efficiently detect the suppression attack in MPL-based LLNs, where each node maintains an increment rate of minimum sequence number in the Seed Set, and compares the recent increment of sequence numbers within a time period with the heuristically calculated increment threshold of sequence numbers to detect potential multicasting misbehaviors. Extensive simulation results show high detection rate and packet reception rate but low false detection rate. Thus, the proposed scheme is a viable approach against the suppression attack in MPL-based LLNs. Since radio propagation and its channel dynamics cannot easily be captured by simulation models, we plan to develop a small-scale testbed and deploy a real network in an indoor office environment to see the full potential of the proposed countermeasure.