系统误差是影响机载LiDAR系统精度的主要因素,因而消除或削弱系统误差影响、提高数据精度具有重要理论意义和工程实用价值。提出基于最小高程差(LZD)的机载LiDAR航带平差方法,并通过引入高斯-马尔柯夫模型提高了平差精度。实验部分考察了引入高斯-马尔柯夫模型的必要性及算法精度。实验结果表明:引入高斯-马尔柯夫模型可有效地提高算法精度;使用LZD进行机载LiDAR航带平差获取的结果均可以满足工程生产的精度需求;与商业软件TerraMatch相比,LZD的精度和TerraMatch的精度相当。

Systematic errors are the main factors affecting the accuracy of airborne LiDAR system. To attain high-precision airborne LiDAR data, it is of great theoretic and practical value to research the key techniques and methods to eliminate these systematic errors. In our paper we propose a new method for airborne LiDAR strip adjustment based on least Z-difference(LZD) algorithm and then introduce the Gauss-Markov model to improve the adjustment accuracy. Experimental results show that after reasonable parameters configuration of the Gauss-Markov model, our improved strip adjustment method can significantly improve the adjustment accuracy. The accuracy of airborne LiDAR data strip adjustment based on LZD can meet our project accuracy requirements. Compared to the commercial software TerraMatch, the LZD and TerraMatch accuracy are at the same level.