Multi-Dimensional Information Association of Vehicular MIMO Radar Based on Tracking Algorithm

In the application of vehicular MIMO (Multiple Input Multiple Output) radar, it is particularly important to measure and associate the position and velocity of targets. However, traditional methods like 3D-FFT have low angular resolution, and velocity ambiguity resolution is required. Combined with Super-resolution DOA (Direction Of Arrival) algorithm, we propose a multi-dimensional information association method based on target tracking, which uses the labeled GM-PHD (Gaussian Mixture Probability Hypothesis Density) algorithm. This method simultaneously completes the association task about position and velocity and the tracking task, and does not require an additional step on velocity ambiguity resolution. Finally, we use experimental data to verify the effectiveness of the algorithm.