一种改进的GPS随机模型建模方法

An Improved Method for GPS Stochastic Modeling

针对观测序列的异方差和时相关特性相互影响但又难以并行建模的问题,提出了一种迭代、序贯处理异方差和时相关问题的随机模型建模方案。实验结果显示,该方法较好地解决了异方差和时相关特性无法并行建模的难题,极大地消除了多路径及系统残余误差对GPS定位成果的影响,增加了基线数据处理的可靠性。

Heteroscedastic and time correlation characteristics of the GPS observation sequence are the main error structures for GPS stochastic modeling. When coping with such problem, the most difficult thing is that the abovementioned two factors could not be well taken into account at the same time. That is to say, stationary process or widely stationary process is the basic requirement when dealing with the time correlation analysis; and analogously, time independent is also the prerequisite to deal with the variance evaluation. To overcome such problem, a new method is proposed. With this method, the heteroscedastie and time correlation characteristics are needed to be considered in sequence. The experimental result proves that the method is correct; and also it shows that the positioning result and the corresponding reliability are greatly improved by the proposed method.