A Velocity Ambiguity Resolution Algorithm Based on Improved Hypothetical Phase Compensation for TDM-MIMO Radar Traffic Target Imaging

In principle, the imaging millimeter-wave radar based on time-division multiplexing multiple-input multiple-output (MIMO) technologies can provide richer target information for intelligent transportation systems due to the high-density target point cloud output. However, the chirp repetition interval extension reduces radar's inherent maximum detectable velocity, leading to the unavoidable problem of estimating the target velocity with a large ambiguity period in imaging radar moving target surveillance applications. To alleviate these problems, we propose an improved hypothetical phase compensation algorithm. Unlike the original method of determining the Doppler ambiguity period by comparing the peak amplitude of the angular power spectrum in each hypothetical case, the proposed algorithm selects the peak of the angular power signal-to-noise ratio (SNR) spectrum as the processing object and jointly decides the target speed by the average of the two highest wave peak intervals in the SNR variation curve. Simulations and practical experiments show that the improved algorithm has higher anti-interference performance. In particular, the proposed algorithm can remain continuously effective when multiple targets or angle information exist in the same distance Doppler cell, making it more suitable for MIMO imaging applications.