A Room Boundary Detection Method Based on a 2D Turntable Millimeter-Wave Radar

Room boundary detection holds significant application value in fields such as smart homes and architectural design. This paper propose a room boundary detection method based on a self-designed two-dimensional turntable millimeter-wave radar system. The method leverages the radar's rotational movement to capture indoor local instantaneous imaging results from multiple directions. Through data fusion, a global point cloud map is constructed. The density-based spatial clustering of applications with noise (DBSCAN) algorithm is then applied to extract the centroids of the boundary point clouds, which are subsequently used to reconstruct the room boundary. Experimental results demonstrate that the proposed method accurately detects room boundaries in various room environments and at different positions within the same room, achieving high precision and consistency. This method is suitable for practical room boundary detection applications.