Research on GPS geometry-based observational stochastic error model - Taoyun ZHOU; Baowang LIAN; Dongdong YANG; Yi ZHANG; Chenglin CAI (Tongxin xuebao)
Aiming at the problem of not enough influencing factors were considered in traditional methods,a much more realistic stochastic model was built.In which error corrections were introduced into the geometry-based function model,an improved least squares variance component estimation (LS-VCE) algorithm with space-for-time was used to solve the model,two sets of real GPS data were collected to evaluate the performance of the model,and with which the carrier phase integer ambiguity was solved.The experimental results show that the proposed methods are superior to the traditional methods in terms of model accuracy,model solution complexity and integer ambiguity resolution.