Abstract
In order to improve the performance of target tracking and solve the defects of unscented Kalman filter, a target tracking algorithm based on improved unscented Kalman filter is proposed in this paper. Firstly, the fading factor is introduced into the filter based on strong tracking filter to avoid the filter divergence, and then wavelet transform is used to estimate the statistical characteristics of measurement noise to improve unscented Kalman filter tracking ability, finally the simulation experiment is used to test the performance of algorithm. The results show that the proposed algorithm increases adaptive ability of target tracking, and obtain good performance for weak maneuvering and non maneuvering target tracking, and fastens the tracking speed.
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