Optimization Algorithm of Bearings Only Tracking based on Cubature Kalman Filter

Abstract

Abstract In view of the shortcomings of low precision and poor performance in the process of bearings only tracking (BOT) in wireless sensor networks(WSNs), an optimization algorithm of BOT based on the cubature Kalman filter(CKF) in WSNs is proposed. The sensors with spatial distribution are divided into several clusters, the number of sensors in each cluster is the same, and each sensor detects data to form a local estimation. Then uploads it to the cluster head (CH) node data fusion, so as to get the accurate information of the target. In order to improve the positioning accuracy, the CKF is used to process the data of each sensor, and then it is uploaded to the CH node to ensure the tracking ability of the filter to the changes of structural parameters. The CH node uses weighted data fusion algorithm to get the final fusion result. The simulation results verify the effectiveness of the method.