DETECTING THE UNKNOWN STEPWISE CHANGE OF THE GAUSSIAN PROCESS BANDWIDTH
The maximum likelihood algorithm is introduced for detecting the abrupt change of the bandwidth of a fast-fluctuating Gaussian random process. This algorithm can be technically implemented much simpler than the ones obtained by means of common approaches. The technique for calculating the characteristics of the synthesized detector is presented and the closed analytical expressions for the type I and II error probabilities are found through the multiplicative and additive local Markov approximation of the decision statistics and its increments. It is established that the presented algorithm for detecting the abrupt change provides a better performance when the bandwidth is stepwise increasing in contrast with when it is stepwise decreasing. By statistical simulation methods, it is confirmed that the considered method of the statistical analysis of the random processes with the abrupt changing characteristics is operable, while the theoretical formulas describing the quality and efficiency of detecting the bandwidth of abrupt change approximate satisfactorily the corresponding experimental data in a wide range of the parameters of the analyzed process. The additional analysis demonstrates that the detectors synthesized by means of the proposed approach can also be used when receiving low-frequency fast fluctuating non-Gaussian random processes with the unknown piecewise constant frequency parameters, without conspicuous losses in the performance