摘要
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,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。
Classical adjustment function only contains nonrandom parameters, it has great limitations to adjustment problem with stochastic parameters. Therefore in GPS elevation fitting, this paper applied least-square collocation model to solve the problem, and compared the least squares fitting configuration in two schemes with those of the quadric surface fitting method. The results show that the least squares collocation fitting residual error is small, the precision is high and elevation fitting effect is better.
出处
《地矿测绘》
2015年第3期3-6,共4页
Surveying and Mapping of Geology and Mineral Resources
基金
2011年度安徽高校省级自然科学研究资助项目"分布式城市雨洪调控模拟模型研究"(KJ2011Z288)
关键词
最小二乘配置
高程拟合
高程异常
随机变量
least squares collocation
height fitting
height anomaly
random variable
