Adaptive Fading Memory Unscented Kalman Filter Algorithm for Passive Target Tracking

作者：Liu Yucheng^*; Liu Yubin

来源：Sensor Letters, 2013, 11(11): 2110-2113.

DOI：10.1166/sl.2013.2951

• Bearings-Only Target Tracking
• Nonlinear Filtering
• Fading Memory
• Unscented Kalman Filtering Algorithm

Aimed at the characteristics of the nonlinear and weak observability of the underwater passive target tracking problem, and combined with the two major factors known as the model error and calculation error which leads to the divergence of UKF algorithm, a kind of the adaptive fading memory UKF algorithm is proposed. The proposed algorithm combines UKF algorithm with the attenuation factor and the adaptive factor. Theoretical analysis and simulation results show that the proposed algorithm is obviously better than UKF algorithm in the filtering precision, stability, convergence time and it can effectively control the influence of model error on the filter solution.

• 出版日期2013-11
• 单位重庆大学; 攀枝花学院