Research On Adaptive Tracking Algorithm Of Radar Multi-maneuvering Targets

With the increasingly complex application environment of modern radar,there are more and more targets and interferences in the detection area,and the tracking targets show the characteristics of diverse types,complex trajectory and maneuverability.These complicated situations bring severe challenges to radar target tracking.Therefore,how to track multiple maneuvering targets accurately and quickly under a large amount of clutter interference is a key problem to be solved urgently in the process of radar target tracking.Aiming at the above key problems,this paper explores a set of adaptive processing algorithm for multi-maneuvering target tracking from two perspectives of improving accuracy and reducing computation.Specific research work is as follows:(1)Firstly,in order to solve the problem of combination explosion in Joint Probability Data Association(JPDA),a Fast Association of Fuzzy Probability Data(FPDFA)algorithm was proposed.The correlation degree between tracking target and echo is described synthetically by using various compact degree fuzzy evaluation functions.The joint incidence probability is used to replace the combined event probability to avoid the splitting of the confirmation matrix.At the same time,the joint correlation probability of common echo and missed test is attenuated,and the influence of common echo and missed test on data interconnection is reduced.Experiments show that FPDFA algorithm not only greatly reduces the computation time,but also ensures high tracking accuracy.In order to solve the problem of track correlation failure caused by the abrupt change of maneuvering target state,an adaptive method of correlation gate is given by referring to the speed-adding process noise form of the "Current Statistics"(CS)model.The experiment shows that the FPDFA algorithm can improve the tracking error of the maneuvering target when the acceleration is abrupt.(2)The multi-objective adaptive tracking model is optimized and improved.An Improved Fuzzy Adaptive Current Statistical Model(IFACS)was proposed to solve the tracking defects of Adaptive Current Statistical Model(FACS)when the Adaptive Current Statistical Model(FACS)responded to the abrupt change of the acceleration of the maneuvering target.A modified logistic fuzzy membership function is reconstructed to improve the response speed of the filter gain to the target state mutation.Based on the acceleration noise model,the recursion relation between maneuvering frequency and target acceleration is derived,and the maneuvering frequency is corrected in real time.The accumulated residual error is used to adjust the gain of acceleration extremum to improve the tracking synchronization rate.The simulation results show that IFACS can effectively improve the tracking accuracy of the maneuvering target with sudden acceleration.