一种基于观测值域的GNSS伪距多粗差验前探测方法

A Method of GNSS Pseudorange Multiple Outlier Prior Detection Based on Observations Domain

采用基于最小二乘的统计假设检验方法进行GNSS伪距多粗差探测时,粗差观测值难以区分,往往造成粗差的转移。针对这一问题,文中提出了一种基于观测值域的GNSS伪距多粗差验前探测方法。该方法无需进行参数估计,且构造的粗差检验量相互独立,避免了粗差之间的相互影响。采用IGS数据分析了粗差检验量的统计特性并对该方法探测多粗差的性能进行了验证。实验表明,该方法可以准确探测出多粗差,对探测出的粗差观测值进行降权处理,可以显著改善受多粗差影响的单点定位的结果。

It is difficult to distinguish gross error observations when conducting GNSS multiple outlier detection using a statistical hypothesis test method based on least squares.To solve theproblem,a new priordetecting method is proposed in this paper.The detecting measures are gaussian distribution and independent to each other.Thus multiple gross errors can be simultaneous exactly located by testing normality of the detecting measures.An experiment on the method is conducted with IGS data.Results are as follows:First,the detecting measures conform to normal distribution confirmed its good outlier detectable characteristics;Second,the multiple outlier detecting results showed over92%detection rate of this method;Atlast,theSPP results influenced by multiple gross errorswere significantly improved byreducing the weights of identified error observables.