Research On Radar Target Data Association And Tracking Algorithm Based On Information Entropy

With the rapid development of radar technology,radar target data association and tracking algorithms have been one of the most important topics studied by scholars.For decades,many scholars at home and abroad have conducted in-depth research on data association algorithms,exploring more efficient,more applicable,more accurate improvements and optimizations,and have achieved very fruitful research results.These achievements are widely used in various defense radars and civil radars that are increasingly mature and available.Modern warfare has put forward higher requirements for radar.In terms of radar data processing,the pursuit of tracking accuracy,tracking real-time and tracking reliability will be more demanding,and the field of civilian radar target tracking will also pay more attention to the cost of tracking algorithms,Tracking stability and real-time.This paper introduces the status of important theoretical researches and important and difficult issues in radar target data correlation and tracking,as well as several typical target tracking data correlation algorithms,commonly used target tracking motion models,and several typical target tracking filtering algorithms.The research focuses on the nearest neighbor data association algorithm and joint probability data association algorithm in the data association algorithm.In the nearest-neighborhood data association algorithm,in-depth research and analysis of known related information yields new available information,and uses this information to improve and optimize the association criteria in the algorithm,which improves the tracking of the algorithm to a certain extent Precision and tracking effect.At the same time,in the joint probability data association algorithm,in order to solve the problem of the explosion of the calculation amount of the algorithm,the related algorithms in the field of fuzzy clustering are used to avoid the split operation of the confirmation matrix.The fuzzy clustering algorithm is used multiple times to ensure the tracking accuracy.In the case of basically unchanged,the tracking time of the data association algorithm is greatly shortened,and the target tracking accuracy and tracking real-time performance of the algorithm under multi-target tracking are better realized.Finally,the improved joint probability data association algorithm is applied to the CS model,and the tracking real-time performance of the improved algorithm is verified by simulation,and the tracking accuracy is simulated and compared.