A millimeter wave radar target tracking method based on inter-frame fusion algorithm

Millimeter-wave radar has become one of the mainstream sensors applied in the field of target tracking research because of its high accuracy, low cost, and non-intrusive nature. Millimeter-wave radar can solve the user's concern about privacy leakage. In this paper, a millimeter wave radar target tracking and recognition method based on an interframe fusion algorithm is proposed. The fusion algorithm is the combination of the DBSCAN algorithm and GMM algorithm. The method first combines multi-frame point cloud data and then compares the fusion algorithm with the DBSCAN algorithm. The multi-frame merging method with frame sequence features solves the problem of sparse radar point cloud data. The fusion algorithm not only solves the problem of noise and target recognition confusion but also solves the problem of DBSCAN identifying multiple clusters into one cluster in an indoor multi-target scene. The result shows that the fusion algorithm improves the recognition accuracy of target tracking compared with the original algorithm and can be applied to the indoor multi-target tracking and recognition scene.