DBSCAN Clustering Algorithm of Millimeter Wave Radar Based on Multi Frame Joint

Millimeter wave radar has been widely used in automatic driving in campus and other park environments. Aiming at the problem that the traditional DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm is difficult to remove multipath noise and distinguish target points from noise, a DBSCAN clustering algorithm based on multi frame joint was proposed. The algorithm was divided into two steps: data preprocessing and merging clustering. By preprocessing the analysis of data features, we could remove the static trivial clusters corresponding to road structures such as guardrails and trees, and only focused on the moving targets in the field of view of the radar system. In the merging process, the multi frame data was merged into one frame, and the speed feature and frame order feature were introduced, which increased the density of the desired target and the dimension of the data. When DBSCAN clustering was performed on the merged data, the multipath noise irrelevant to the position change with time could be removed. Through experiments in different scenarios, it was proved that this method has different degrees of improvement than the traditional method.