Abstract
Range/Doppler migration and velocity ambiguity are two well-known problems encountered in high-speed moving target detection using a linear-frequency-modulated continuous-wave automotive radar. To mitigate the problems, we introduce a simple Doppler–range processing (DRP) algorithm by first performing Doppler processing via fast Fourier transform (FFT) across slow-time samples, followed by a simple interpolation step, and then range processing via FFT along Doppler migration lines over fast-time samples. The proposed DRP algorithm can achieve full range and full velocity resolutions, as well as full coherent integration gains. It attains a computational complexity comparable to that of the conventional 2-D-FFT-based range–Doppler processing approach, computationally much more efficient than existing approaches. The proposed DRP algorithm can automatically resolve the velocity ambiguity problems. We analyze its velocity ambiguity mitigation capability in relation to the radar bandwidth and the number of slow-time samples within a coherent processing interval. The effectiveness and the computational efficiency of the proposed algorithm are demonstrated by numerical examples.
Highlights
Range/Doppler migration and velocity ambiguity are two well-known problems encountered in highspeed moving target detection using linear frequencymodulated continuous wave (LFMCW) automotive radar
We further prove that the proposed DopplerRange Processing (DRP) algorithm can automatically resolve the velocity ambiguity problem, and we analyze its velocity ambiguity mitigation capability in relation to the radar bandwidth and the number of chirps, i.e., slow-time samples, within a Coherent Processing Interval (CPI)
We have investigated the range/Doppler migration and velocity ambiguity problems of high-speed moving target imaging using LFMCW automotive radar
Summary
Driving [1] and advanced driver-assistance systems (ADAS) [2]. Unlike lidar and camera, radar has minimal performance degradations under various weather conditions or in dust, smoke and other obscurants, and has become an indispensable sensor for modern vehicles [3]. The RFT and the focusing methods must perform brute-force integration over slow-time samples for each candidate (range, velocity) pair within the imaging area, resulting in a prohibitive computational complexity Another well-known problem encountered in automotive radar applications is the velocity ambiguity of high-speed targets. This method first performs Doppler processing via FFT over slow-time samples, followed by a simple interpolation step, and range processing via FFT along Doppler migration lines over fasttime samples We demonstrate both theoretically and numerically that the proposed DRP algorithm can achieve full range and full velocity resolutions, as well as full coherent integration gains, while attaining a computational complexity comparable to that of the conventional RDP approach.
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