The Application Reserch Of Calculation Of The Semi Parametric Model In Short Baseline With Large Height Difference

High precision GPS positioning generally uses the double difference (DD) method to eliminate and weaken all kinds of errors and improve the accuracy of the baseline solution. Although the baseline is short, the tropospheric delay cannot be fully eliminated by using DD method if the height difference of two stations is very large. Thus, the error of float ambiguity solution will be large as well as be difficult to be fixed. It will even cause the failure of baseline solution if the residual tropospheric delay caused by the height difference is too large. In the parametric model, parameters are not be used to consider the influence of the residual tropospheric delay. The error of the model is inevitable if the existing parameter models are used to describe the observations. In this dissertation, semi-parametric model is proposed to solve the short baseline with large height difference and weaken the residual tropospheric errors. Actual experimental results show that, the semi-parametric model can separate residual tropospheric error and improve calculating precision of baseline better than the least squares estimation. The main research contents of study are as follow:1. The semi-parametric model of GPS static relative positioning. Semi-parametric model is proposed to solve the short baseline with large height difference on the basic of fixed ambiguity. The key to the use of the semi parametric model is to select the proper regularization matrix R and the regularization parameter a. The time series method is used to determine the regularization matrix R, and the regularization parameter a is determined by the L-curve method in this paper. The Saastamoinen model is chosen as the tropospheric delay correction model, and the NMF function is chosen as the mapping function. Actual experimental results show that the semi-parametric model can separate residual tropospheric error, improve calculating precision of baseline as well as is better than the least squares estimation.2. GPS single epoch ambiguity resolution. For carrier phase ambiguity is difficult to be fixed or fixed in error when solving the short baseline with large height difference by single epoch, the partial search algorithm is used to solve the ambiguity, and the comparison with the conventional LAMBDA method is carried out to verify the superiority of the proposed algorithm.3. The semi-parametric model of GPS single epoch relative positioning. The general compensated least squares for semi-parametric model is proposed to solve the short baseline with large height difference by single epoch, the partial search algorithm is used to solve the ambiguity combined with LAMBDA method and the ridge parameter method based on Helmert variance components estimation is used to determine ridge parameter. Actual experimental results show that, the semi-parametric model can separate residual tropospheric error and improve calculating precision of each direction up to mm grade better than the least squares estimation.