A Millimeter-Wave Radar Tunnel Obstacle Detection Method Based on Invalid Target Filtering

Abstract

Underground obstacle detection is the premise of unmanned driving. Aiming at the problem of obstacle detection in coal mines using a millimeter-wave radar, this paper proposes a filtering algorithm for invalid targets in roadways. Firstly, the target information output by millimeter-wave radar is analyzed, and the obstacle information of the underground roadway is extracted. Then, the filter algorithm is used to filter the resolved empty targets, false targets and non-potentially dangerous targets. The empty target whose target distance is zero in radar data is filtered directly. The pseudo targets generated by the radar performance or the instability of the echo signal are filtered through the radar-effective target life cycle method. The non-threatening targets beyond the horizontal range threshold and longitudinal range threshold are filtered directly. The experimental results show that the average filtering rate of the algorithm is more than 87.82% in the static state. When the speed is 5 km/h, the average filter rate is 87.70% for smooth driving and 86.83% for uneven road surfaces. When the speed is 7 km/h, the smooth driving rate is 87.54%, and the uneven road surface is 86.56%. When the speed is 10 km/h, the smooth driving rate is 86.50%, and the uneven road surface is 86.44%. Although the filter rate decreases with the increase of speed or vehicle vibration in the running state, the average filter rate of the proposed algorithm can reach more than 86% under all conditions.