Research On Automotive Radar Signal Processing Algorithm

Automotive radar is the core of active safety of automobiles.It has become an indispensable key technology in the field of intelligent transportation.It is widely used in advanced driver assistance systems and driverless vehicles.In order to seize the opportunity of widespread application of automotive radar,it is necessary to accelerate the pace of research on vehicles.It is necessary to speed up the research of automotive radar signal processing technology and further promote the development of automotive radar.Therefore,this paper studies the problem of automotive radar signal processing and verifies the algorithm based on the hardware platform.First,the basic principles of automotive radar are introduced.In the traditional frequency modulation continuous wave frequency modulation(FMCW)system,there are many false targets in the target detection.The FMCW waveform design scheme based on multi-segment modulation is proposed.With the screening of target velocity on the basis of the constant frequency and obtaining the target information through the LFM,target pairing is implemented for two times to eliminatethe false target.Theoretical analysis and simulation results show that the multi-segment modulation waveform proposed in this paper can effectively reduce false targets in multi-target environments.Then,the automotive radar signal preprocessing algorithm is studied.The I/Q signal imbalance compensation algorithm solves the problem of image frequency and DC component in the hardware platform,which is the basis for the subsequent signal processing.In order to improve the detection ability of the system for weak targets,the pulse compression and signal accumulation algorithms are studied,and the applicability of the two algorithms is discussed based on the hardware platform.In order to extract the frequency information of the target,the Cell Averaging Constant False-Alarm Rate(CA-CFAR),the Greatest Of Constant False-Alarm Rate(GO-CFAR),the Smallest Of Constant False-Alarm Rate(SO-CFAR),and Order Statistics Constant False-Alarm Rate(OS-CFAR)were used for simulation verification and comparative analysis.Finally,the accuracy of automotive radar ranging in multi-target environment is susceptible to inter-spectral interference.A multi-target distance estimation algorithm based on iterative interpolation is proposed.The FFT and CFAR are used to estimate the number of targets and the rough position of the target,then non-uniform iterative interpolation of the target spectrum,and inter-spectral interference is eliminated during each iteration to obtain a more accurate distance.The simulation results show that the proposed algorithm has higher estimation accuracy under multi-objective environment and low SNR.Based on the 24 GHz automotive radar system,the multi-section modulation waveform,I/Q signal imbalance compensation algorithm,signal accumulation algorithm,CFAR algorithm,multi-target distance estimation algorithm and single-pulse angle measurement algorithm are studied.