Research And Simulation Of Radar Group Target Tracking Algorithm

The use of radar measurements to track targets as much as possible is a matter of great concern.Due to different factors such as radar capability,environment and the nature of the object being tracked,the solutions vary greatly.Moreover,radar tracking is a key technology in the fields of military defense,monitoring,and automatic driving,so it has high research value for target tracking algorithm and simulation research of typical radar systems.Radar target tracking is a large research direction.Thesis focuses on the traditional radar multi-target tracking and new radar tracking,Thesis studies the traditional radar target tracking method and the new radar tracking algorithm from the theoretical derivation and computer simulation.The main research contents are as follows:1.For multiple target tracking are discussed,focused on the theoretical derivation and simulation of data correlation algorithm,and based on multiple target tracking application,emphatically to Ji Sao small low altitude target designation radar,airborne early warning radar,radar seeker and a shipboard radar simulation,analyzed the different application scenarios,the use of multiple target tracking methods and effects.On this basis,multi-target tracking simulation is carried out by using the measured data of lowaltitude small-target indicating radar,and the effectiveness of the algorithm is verified.2.On the basis of the traditional tracking algorithm,target tracking and waveform design are related,and three cognitive tracking algorithms based on waveform optimization under different environments and criteria are studied.The kalman filter cognitive tracking algorithm based on waveform optimization is discussed in noise environment.In clutter environment,a probabilistic data association cognitive tracking algorithm based on waveform optimization is studied.An interactive multi-model cognitive tracking algorithm based on waveform optimization is proposed for maneuvering targets.Finally,three algorithms are simulated,and the simulation results verify that the cognitive tracking algorithm has obvious advantages in improving the tracking accuracy.3.The Koch method,Feldmann method,IMM-Feldmann method,LAN method,IMM-LAN method and other five extended target/group target tracking algorithms based on random matrix are studied.On this basis,an improved method with additional extended parameters is proposed.The rotation rate and expansion rate in the extended dynamic model are modeled separately.In order to cope with the goal of changing direction and size,the algorithm is compared with the previous five algorithms.Finally,the simulation analysis of the drone swarm tracking of the two formations is carried out,and three indicators,such as long wheelbase,long and short axis ratio and center estimation error,are proposed as criteria according to the characteristics of the drone swarm.