最小二乘配置模型在 GPS 高程拟合中的应用

摘要

Classical adjustment function only contains nonrandom parameters, it has great limitations to adjustment problem with sto-chastic parameters, therefore in GPS elevation fitting, this paper use least-square configuration model to solve the problem, and com-pared the least squares fitting configuration in two schemes with those of the quadric surface fitting method, the results show that the least squares configuration fitting residual error is small, the precision is high and elevation fitting effect is better.%经典的平差函数模型中只含有无先验统计信息的非随机参数，而针对附有随机参数的平差问题具有很大的局限性，为此在GPS高程拟合中，本文用最小二乘配置模型解决了这一问题，并且通过实际算例，设计两种最小二乘配置拟合方案与二次曲面拟合法进行了比较，结果表明，最小二乘配置拟合残差较小，外符合精度较高，高程拟合效果更好。