Vehicle Targets Detection In Complex Scene Based On Airborne LiDAR

The Airborne Lidar is a kind of sensor that can acquire3D surface information of thetarget. The laser radar scanning will produce a large number of three-dimensional data.How to deal with these three-dimensional data and extract useful information from them isan important part of the laser radar system. The main work of this paper is to study vehicletargets detection method in a relatively complex context of.The main contents are asfollows:(1) With regard to the three-dimensional laser radar data acquisition part, thecoordinate systems of the airborne laser radar systems and their mutual conversion methodof the coordinate systems is studied. In consideration of the fact that the point clouddistribution of different objects differs with each other, point cloud distribution of sometypical objects are discussed. Also a new scanning system is introduced. The point cloudrecovery algorithm that converts raw data to the specific coordinates is studied too.(2) Three-dimensional laser point cloud data organization is the basis of thethree-dimensional laser data processing. Firstly, several common point cloud dataorganization methods are discussed, and their advantages and disadvantages are compared.For point cloud data processing, we study point cloud feature, point cloud filtering, spatialclustering algorithm. Point cloud data processing is the basis of the vehicle target detectionmethods.(3) Local elevation of mutation as well as local flat nature of point cloud is theprimary basis for the vehicle target detection algorithms. Whether there is groundestimation step, the detection algorithm can be divided into a ground-estimation baseddetection algorithm and the feature based detection algorithm. This paper studies a vehicletarget detection algorithm based on the range of the gate. Then a ground-estimation baseddetection algorithm,that is, the AETEW point cloud filtering based detection algorithm isproposed.(4) Finally, making an analysis of several vehicle target detection performance of theAETEW point cloud filtering based detection algorithm by experiments, including of thescene adaptive ablility and the scene resolution, the scene noise on the detection performance.