A new self-tuning Kalman filter for tracking abrupt input change
Xuwen Li, Qiang Wu, Shuicai Wu · 2011
This paper proposes a new self-tuning Kalman filter with good tracking ability for unknown noise statistics and unknown abrupt input change. The new filter can easily compute unknown abrupt input and steady-state gain matrix by building up online identification of ARMAX innovation model in real time. The simulation results of tracking a maneuvering target shows the effectiveness of the new method in this paper.