Research On Multi-target Detection And Tracking Technology Of FMCW Radar

Frenquency-modulated continuous wave(FMCW)radar is widely used in military and civil fields because it has the advantages of high range resolution,simple structure,and low power consumption.Radar detection and tracking are the core tasks of radar signal processing and data processing respectively.After receiving reflected signals,a radar needs to process received signas to make decisions on if targets are present,and estimate distance,speed,angle and other information for each target.Then radars need to perform data processing(filtering,data association and other processing)to implement target tracking.Data association is one of the key technologies of data processing,which is challenging for environments with noise,heavy clutter and mutli-targets.Consequently,it is very important to perform data association by making full of prior information available.This thesis introduces the principle and related algorithms of FMCW radar target detection and tracking,mainly concentrates on the data association algorithm in multi-target tracking,and proposes a joint probability data association algorithm based on loss function so as to achieve good tracking performance under limited storage resources and prescribed time constraints.The main work is as follows:First,this thesis introduces the basic principles of FMCW radar ranging and speed measurement,and gives the method of extracting target distance and speed.In addition,the traditional FFT angle measurement method and super-resolution angle measurement methods(MUSIC and ESPRIT)are introduced and anylazed by numerical simulations.Secondly,the filtering of the tracking part and some commonly used data association algorithms are researched and analyzed.A joint probabilistic data association algorithm based on loss function(LJPDA)is proposed so that the computation load and accuracy of the multi-target tracking algorithm can be guaranteed simultaneously.Firstly,data association is divided in to three cases based on the relationship among validation gates and the number of measurements in the overlapping area for validation gates.Also the contribution coefficient is employed for evaluating the contribution of a measurement to a target,and the loss function,which reflects the cost of the new proposed data association algorithm,is defined.Moreover,the equation set of optimal contribution coefficient is given by minimizing the loss function,and the optimal contribution coefficient can be attained by using the Newton-Raphson method.In this way,the weighted value of each target can be achieved,and the data association among measurements and tracks can be realized.In the end,we compare performances of LJPDA proposed and joint probabilistic data association(JPDA)algorithm via numerical simulations,and much attention is paid on real-time performance and estimation error.Theoretical analysis and experimental results reveal that the LJPDA algorithm proposed exhibits small estimation error and low computation complexity.Finally,considering all the steps of radar signal and data processing,this thesis reasonably designs the transmitting waveform,detection and tracking parameters of a FMCW radar according to the practical requirement,and realizes a radar detection and tracking system.