Research On Object Detection And Tracking Algorithm Based On Millimeter Wave Radar Sensor

With the rapid development of radio technology,millimeter wave radar has gradually become an important research field in intelligent transportation systems.Millimeter wave radar sensor plays an important role in the intelligent transportation system because of its strong anti-interference ability,high precision and long-distance measurement.The moving target detection and tracking algorithm is one of the most important technology in the field of intelligent traffic monitoring,and is the key to real-time intelligent traffic monitoring.As the research background of intelligent traffic monitoring system based on millimeter wave radar,target detection and tracking algorithms are studied,in this paper,which includes the following three aspects:Firstly,basic principles of radar systems,including radar equations,basic composition of the radar and the operating frequency are introduced.Then doppler theorem in millimeter-wave radar signal detection methods,frequency-modulated continuous(FMCW)millimeter radar,millimeter-wave radar speed measurement and ranging technology are introduced as well.Finally,basic principles of moving target detection and tracking are introduced,which provide theoretical basis for algorithm research and simulations in later chapters.Secondly,the constant false alarm detection algorithm in millimeter wave radar target detection is studied.The SVI-CFAR detection algorithm is improved for the false alarm,missed alarm and multi-target interference problems of the commonly used millimeter wave radar constant false alarm detection algorithm in multi-target environment,uniform or background clutter environment.Through the Monte Carlo experiment,the improved NSVI-CFAR algorithm is compared with various detection methods such as SVI-CFAR.The simulation is verified by Matlab.The results show that the improved NSVI-CFAR method maintains good detection probability and false alarm probability in uniform environment and background clutter environment,and can improve the detection performance under multi-target interference environment.Thirdly,the Kalman filter algorithm in target tracking of millimeter wave radar is studied.Principle of data fusion association between target detection and target tracking is introduced.For the problems of target interference,accuracy and uncertainty in the target tracking process,the Kalman filter algorithm is applied to in linear state,and the iterative extended Kalman filter algorithm is applied in the nonlinear state.The performance of Kalman filter algorithm in target tracking is analyzed by Matlab simulation.The results show that the linear motion state Kalman filter tracking algorithm has small error,and the iterative extended Kalman filter algorithm also demonstrate small error in nonlinear dynamic model.