无检校场的机载LiDAR点云数据检校方法

Calibration of airborne LiDAR cloud point data with no calibration field

机载激光雷达(light detection and ranging,LiDAR)是集合了多种技术的集成设备,其系统误差对后期产品的影响较大,因此必须对其进行误差检校。传统的检校方法可靠稳定,但对检校场地要求较高,在某些地区难以找到合适的检校场地。基于此,提出一套无检校场的点云检校方法。该方法基于Burman模型和航带平差理论,通过安置角及三维坐标的改正来消除或减少系统误差。对云南小江实验区的验证结果表明,检校后的点云成果数据完全满足1∶2 000比例尺DEM成图要求。

The airborne LiDAR system integrates the global positioning system （ GPS） , inertial navigation system （ INS） and Laser Ranging system. Nevertheless, in the process of measuring the system, many errors are inevitably produced, and hence the influence of the observational error caused in the process of measurement must be considered and eliminated, which is called data calibration. The traditional calibration method is stable and reliable, but its disadvantage is that the calibration field flight is requisite, and it has a higher demand for ground objects. In some areas it is difficult to find an appropriate calibration field. In view of such a situation, the authors employed a calibration method of cloud data without calibration field, which is based on Burman model and stripe adjustment theory; through the Placement Angle correction and 3D coordinate correction, it can eliminate the systematic error. Tests in Xiaojiang experimental area of Yunnan Province show that the cloud point data after calibration can completely meet the 1∶2 000 DEM mapping precision.