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

机译:机载3D成像LiDAR像素参数滚动仿真方法

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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.
机译:机载3D无扫描仪成像LiDAR是一种无需扫描仪机制的主动检测手段,在紧急救援和飞行安全方面具有广阔的应用前景。如何找到合适的像素参数是应用这种方法的关键问题。低分辨率可能无法满足要求,而高分辨率会导致不必要的功耗。本文提出了一种基于任务的滚动仿真方法来获取3D无扫描仪成像LiDAR的像素参数。首先,获得空中物体的识别水平,以进行任务需求分析。然后给出了生成3D点云的方案,以获取3D无扫描仪成像LiDAR的数据。通过应用Zernike矩特征提取算法和相关系数方法,对模拟点云的数据特征进行提取和识别,从而确定识别结果是否满足任务要求。基于案例研究的数值结果,已经证明,通过实施所提出的方法,可以实现满足任务要求的机载3D成像LiDAR的最小像素。

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