Adaptive Unscented Kalman Filter Based on Differential Evolution Algorithm

This paper discusses choice for scaling parameter of the unscented transformation. By analyzing and comparing some scaling parameter selection methods, the scaling parameter is selected as an optimization objective. Differential Evolution (DE) algorithm is applied to the Unscented Kalman Filter (UKF), the optimized scaling parameter leads to the minimum error at each time interval. An adaptive UKF based on DE is proposed. The experiments show that the accuracy of UKF is significantly improved by the adaptive strategy which not only to avoid random divergence with the constant parameter but also suitable for any form of UKF without the constraints of the number of parameters.