Constrained Unscented Kalman Filtering for Bearings-Only Maneuvering Target Tracking  

作　　者：ZHANG Hongwei XIE Weixin 

机构地区：[1]Sun Yat-sen University,Guangzhou 510725,China [2]ATR Key Laboratory,Shenzhen University,Shenzhen 518060,China

出　　处：《Chinese Journal of Electronics》2020年第3期501-507,共7页电子学报（英文版）

基　　金：This work is supported by the National Natural Science Foundation of China(No.61773267);the Science and Technology Program of Shenzhen(No.20170302145519524,No.20170818102503604).

摘　　要：To track the bearings-only maneuvering target tracking accurately online,the soft measurement constraints are implemented into the Unscented Kalman filtering(UKF).To deal with the soft measurement constraints,the Lasso regularization is added as the obstacle function.In doing this,the sampled sigma points can be restricted into the feasible region.To enhance the sampling efficiency,the global optimal solution is acquired by a heuristic optimizer.To smooth the outliers,the posterior distribution is approximated by a Gaussian mixture consists of the original and the modified priors with the fuzzy weighted factor.Simulated results indicate the accuracy and the computational efficiency of the proposed method.

关 键 词：Bearings-only maneuvering target tracking Soft measurement constraints OPTIMAL 

分 类 号：TN713[电子电信—电路与系统]