Rolling Simulation Method for Acquiring Pixel Parameter of Airborne 3D Imaging LiDAR

Airborne 3D scannerless imaging LiDAR is an active detection means without scanner mechanism and has a broad application prospects in emergency rescue and flight safety. How to find appropriate pixel parameter is an critical problem for applying this approach. Low resolution may not meet requirement while high resolution will cause unnecessary power consumption. In this paper, a task-based rolling simulation method is proposed for acquiring pixel parameter of 3D scannerless imaging LiDAR. First, recognition level of aerial object is obtained for task requirement analysis. Then a scheme of generating 3D point clouds is given to acquire data of 3D scannerless imaging LiDAR. By applying Zernike moment´s feature extraction algorithm and correlation coefficient method, the data features of the simulated point cloud is extracted and recognized to decide if the recognition results satisfy the task requirement. Based on numerical results from a case study, it has been demonstrated that, by implementing the proposed approach, the minimum pixels of airborne 3D imaging LiDAR satisfying task requirement can be achieved.