Research And Implementation Of LFMCW Radar Multi-target Detection Algorithm

Linear frequency modulation continuous wave(LFMCW) radar has been utilized widely in some fields because that LFMCW radar has so many advantages in short-range situation. In this paper, working principle and practical application of the LFMCW radar is studied based on the functional system requirement of LFMCW radar in Ka band, which should have the ability of range and velocity for multi-targets situation. The main research works include:a) The basic working principle, including almost every step of LFMCW radar signal processing is firstly introduced in order to provide a theoretical basis for follow-up study.b) Based on the analysis of the requirement of Ka band radar system, this design a signal processing scheme, Each component element of the LFMCW radar signal processing, including the MTI, the MTD coherent accumulation, the constant false alarm rate(CFAR) detection and the multi-targets pairing algorithms are studied, and the simulation of the radar echo signal processing is carried out using Matlab software. In MTI part, two deferent MTI methods are compared and the result shows the disadvantages of each method. In MTD part, method based on the FFT and method based on the FIR are analyzed. In CFAR part, based on the analysis of the CA CFAR and OS CFAR, a new fast and efficient CFAR method is proposed based the combination of CA and OS, in which case, masking effects in multi-target situations can be avoided without increasing the computation complexity. In multi-targets pairing part, two pairing methods are analyzed and in order to performance and easy to project implementation, this paper completes the multi-targets pairing by the comparing the velocity and the magnitude information of different moving targets.c) Signal processing algorithm of Ka band radar in FPGA is implemented with the Xilinx’s IP core and Verilog language in Xilinx ISE13.3 software integration environment.d) The whole radar system is tested in the practical environment to verify the algorithm used in this paper and project realization based on FPGA. The final test results show that the whole system works well, and it has achieved the measurement of multi-target speed and distance parameters.