| In military research field,detecting moving target has become a hotspot recently.In the field of warfare,targets such as ship-borne missiles and military aircraft are becoming more mobile,and the detection environment is becoming more and more complex.This puts forward more stringent requirements on signal processing for short-range high-speed target detection;In the field of counter-terrorism and medical treatment,micro-Doppler vital signs detection is of great significance.This kind of micro-Doppler life signal has strong randomness.And it is easily interfered by noise,which brings great difficulties to the identification and detection of micro-Doppler life signals.Based on this,this article will conduct in-depth research on the signal processing techniques for the detection of high-speed moving targets and micro-Doppler targets.The main work of this paper is as follows:1.Aiming at short-range high-speed moving targets,taking the millimeter wave LFMCW detection system as the example.A brief analysis of the ranging principle is carried out,and the system parameters are determined.In terms of signal processing,the theoretical introduction and analysis of MTI and MTD are carried out,the MTI and MTD processors are designed,and the relevant design parameters are given.Aiming at the problem that the target may move in distance during signal accumulation,through theoretical derivation,the relationship between the maximum relative motion speed and the number of accumulations is derived.By selecting relevant parameters reasonably,it avoids moving in distance in the detection of short-range high-speed targets.In target detection,the focus is on the detection effects of the three MLCFAR algorithms in uniform and clutter environments.The signal processing algorithm mentioned above is simulated using MATLAB.The result verifies the relevant algorithm is effective for detecting high-speed moving targets.2.Based on the FPGA chip,the signal processing software and hardware is completed,which will be used in short-range high-speed target detection system.The hardware mainly includes the design and debugging of circuits.Such as power supply circuit,A/D circuit,modulation circuits and FPGA minimum system;the software algorithm mainly includes FIR filter,FFT algorithm,signal accumulation algorithm,CFAR detection algorithm,etc.These algorithms are implement on FPGA.Finally,an outdoor fixed-distance experiment was carried out that verified the correctness of the relevant design.3.Aiming at the micro-Doppler target,the human ECG micro-Doppler signal detection is the research object.For the denoising problem of human micro-motion signals,the LMS adaptive filtering algorithm is applyed.The influence of the search step factor in the LMS algorithm on the filtering effect is analyzed through simulation.On this basis,combined with the traditional IIR digital filter,a signal separation algorithm is proposed.The algorithm is based on LMS adaptive filtering.And it can separate breathing and heartbeat signals.The simulation results verify that the algorithm is effective in eliminating noise.And the algorithm can accurately extract human breathing and heartbeat information from it.4.Based on the researched human body micro-Doppler signal detection algorithm,the software and hardware design of the signal processing algorithm is implemented.Mainly including the design of 0.1～10Hz active bandpass filter,amplifier circuit,high-precision ADC circuit,FIFO,digital FPGA implementation of modules such as filters and adaptive cardiopulmonary signal separation.Finally,a continuous wave Doppler radar system was built,and a micro-Doppler signal detection experiment was carried out to realize the detection of human micro-Doppler signals. |
