A UAV target detection method in laser point cloud

Abstract

The UAV target detection method in the laser point cloud of the present invention is mainly divided into four steps: point cloud voxel rasterization, ground point cluster removal, air target point cloud division and UAV target morphological feature screening. This method uses the point cloud imaging of lidar as the original data, and detects low-speed and small UAV targets from it through the intelligent detection method, and through the process of ground point clustering and removal, the ground echo data points generated in the point cloud data ( The ground, bushes, buildings, etc.) are removed to reduce the interference to target detection, making this method especially suitable for low-speed and small UAV targets with low flying heights, optimizing the detection effect, and accurately measuring the target's azimuth angle, The pitch angle, distance, speed, and target size and shape have the characteristics of high precision and fast response, which can improve the positioning accuracy of the target drone to the centimeter level, which is superior to the existing photoelectric, radar and radio detection methods.

Description

technical field [0001] The invention relates to an unmanned aerial vehicle target detection method, in particular to an unmanned aerial vehicle target detection method in a laser point cloud, and belongs to the technical field of unmanned aerial vehicle detection. Background technique [0002] The existing UAV target detection technology is mainly divided into three methods: photoelectric detection, radar detection and radio detection. Photoelectric detection uses an image sensor to image the sky, and then detects the position of the target through machine vision algorithms. The method of measuring the target echo is used to determine the exact position of the target, but it is easily affected by the ground echo when measuring the low-speed and small UAV target with a low flying altitude, and the detection effect is not ideal. Radio detection is a way to passively locate the target UAV by measuring the radio signal emitted by the UAV itself, but its measurement accuracy is ...

AI Technical Summary

Problems solved by technology

Photoelectric detection uses an image sensor to image the sky, and then detects the position of the target through machine vision algorithms. The way to measure the target echo is to determine the exact position of the target, but when measuring the low-speed and small UAV target with a low flying altitude, it is easily affected by the ground echo, and the detection effect is not ideal.

Radio detection is a way to passively locate the target UAV by measuring the radio signal emitted by the UAV itself, but its measurement accuracy is very dependent on the weak radio signal amplitude, and it is also easily affected by the surrounding surface environment. High, only approximate angular orientation can be measured

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