Sequential Joint State Estimation and Track Extraction Algorithm Based on Improved Backward Smoothing

In order to further promote the accuracy of state estimation and track extraction capabilities for multi-target tracking, a sequential joint state estimation and track extraction algorithm is proposed in this article. This algorithm is based on backward smoothing under the framework of Labeled Random Finite Set and utilizes label iterative processing to perform outlier removal, invalid short-lived track removal, and track continuity processing in a sequential manner in order to achieve the goal of improving the multi-target tracking performance of the algorithm. Finally, this paper verifies through experimental simulation and measured data analysis that the proposed algorithm has improved the performance of radar multi-target tracking to a certain extent.