为满足机载激光雷达系统测量精度需求，研究了激光雷达与导航系统安装偏差参数的标定问题。首先，利用激光雷达反射强度信息确定和检测控制区，通过控制区平均获取对应的控制点，并根据控制点量测构造包含偏差参数和导航参数信息的激光矢量量测方程。然后，利用广义最小二乘法对噪声进行白化操作。最后，进行最小方差准则下的内方位参数估计。实验结果表明，该算法能够有效抑制系统矩阵不精确的影响，安装角估计精度＜0.01°，安装杆臂估计精度＜3 cm。与传统方法相比，在量测噪声放大条件下估计精度平均提高了5.27%，在放宽小角度假设条件下估计精度平均提高了6.54%，满足机载激光雷达系统标定在强误差条件下的精度及鲁棒性需求。

The interior origination element biases between a laser scanner and a navigation system were calibrated to satisfy the survey precision requirement of a lidar. Firstly, control areas are detected and ascertained through laser intensity map, and then the control points are calculated with laser footprint measurements averagely within a control area. Equations including biases and navigation parameters based on control points are set up for optimal estimation. The general least square method with a white technology is adopted to handle the coupled noise covariance and to give an optimal estimation of biases under the least square principle. Experiment results show that this algorithm can restrain imprecise coefficient matrix errors caused by a navigation system. The precision of fixing angle biases is superior to 0.01° and the precision of fixing level-arm biases is superior to 3 cm. As compared with traditional methods in general, the average estimation precision has improved by 6.54% under the condition of a relaxed small angle and by 5.27% in the measurement noise to be amplified. These data confirm that the algorithm can satisfy the calibration requirement for both precision and robust under strong noise conditions.