Target tracking based on amendatory Sage-Husa adaptive Kalman Filtering

Aiming at the boundedness of target tracking inaccuracy, even the lost of tracking caused by the error accumulation and state mutation in the aspect of target tracking using Kalman filter. The paper proposes a novel algorithm which is based on the modified Sage-Husa adaptive Kalman filter. This algorithm adjusts the predicted value of Sage-Husa adaptive Kalman filter in time by setting judgment and amendment rules, which can inhibit accumulation of error on target tracking and improve the filter precision in steady state and strengthen the stability and adaptability of filter. The experimental results show that the effectiveness of the novel algorithm.