Estimation Of UAV Movement Parameters Based On TDOA Measurements Of The Sensor Network In The Presence Of Abnormal Measurements

The rapid development of UAV technologies and the wide access to them by various consumers give rise to a new class of threats. To neutralize them, complex UAV protection systems are created, which include passive and active measuring systems. As a passive system, a wireless sensor network is used, which allows to determine location of UAV with high accuracy based on TDOA measurements. However, in real conditions, abnormal (rough) measurement results may appear that lead to divergence of Kalman filtering algorithms for UAV movement parameters.On the basis of a mathematical apparatus of the mixed Markov processes in discrete time, a quasi-optimal algorithm of adaptive estimation of UAV movement parameters based on the TDOA-measurement of the sensor network in the presence of abnormal measurement errors was synthesized. The efficiency analysis of obtained algorithm and its comparison with algorithm of Kalman filtering are performed using the statistical simulation..