Adaptive and Robust Tracking for Radar Maneuvering Targets

The robustness and stability of maneuvering target tracking algorithms based on Kalman filtering are not satisfactory. The state estimation results are relatively ineffective when there exists model uncertainties or turning maneuvers during the target moving. In extreme cases, this may lead to filter divergence. According to this issue, a novel adaptive robust tracking algorithm for radar targets has been proposed in this paper. By using strong tracking filtering strategy, an adaptive fading factor is introduced to adjust the matrix gain in real time for dealing with the model uncertainties and ensuring the tracking effect. The simulation results show that this algorithm has better stability and tracking effect for maneuvering targets.