Higher-order cumulants based maneuver detection in Kalman filter

Maneuver detection is a key issue in multiple-model target tracking applications. In the Kalman filter, the conventional maneuver detection algorithm fails when the maneuver is almost buried in noise. The multiresolution approach behaves well for maneuver detection, but the time delay limits its application. We suggest a new algorithm for maneuver detection based on the third-order cumulant of the measurements. As cumulants are blind to Gaussian noise, the maneuver is easy to detect in the cumulant domain. Using sliding window processing, the maneuver detection algorithm is real-time without any time delay. Simulation results demonstrate the effectiveness of the algorithm over the conventional one, especially at low SNR.