Study On Theory And Method Of Key Issues In Atmospheric Water Vapor Inversion By Ground-Based GPS

The research on atmospheric water vapor inversion by ground-based GPS not only has important significance for weather forecast, but also can improve the precision of GPS positioning, so as to display potential in the application of GPS. The main problems related to atmospheric water vapor by ground-based GPS inversion were systematically researched in this thesis. The main research contents and innovation points were summarized as follows:1. Research status of the main problems which influence atmospheric water vapor inversion by ground GPS were outlined, and the research goals were pointed out in this thesis, the GPS observation model and estimation method were introduced in detail, so as to lay a foundation for subsequent data processing.2. The broadcast ephemeris extrapolation accuracy of satellite orbit was analyzed,and the methods of Lagrange interpolation, Neville interpolation, Chebyshev and Legendre polynomial fitting applied to precise ephemeris were introduced in this dissertation, through calculation of actual precision ephemeris data, the calculations of precise ephemeris in interpolating and fitting from the order, accuracy and computational efficiency were analysed comparatively, and the best order of the interpolation algorithm and the fitting algorithm of the position error comparison chart and the accuracy of all the satellite figure contrasts were given. And then, two kinds of calculation methods of satellite signal launch time and the earth’s rotation error influencing satellite orbit were respectively analyzed by each numerical example.3. The characteristics of GPS observation data cycle slips detection based on TurboEdit algorithm, fixed length sliding window fitting model has been designed, which makes the improvement to Geometry-Free combination method, using the least square Chebyshev polynomial fitting to repair cycle slips after cycle slips detection is proposed in the dissertation. The experimental results show that the improved TurboEdit algorithm can detect equal-cycle such as one cycle of small cycle slips, big cycle slips and continuing happened small and big cycle slips, at the same time, the least square Chebyshev polynomial fitting can also repair cycle slips more precisely.4. Base on cycle slips act as gross errors after differencing between adjacent epoch in double difference observation sequences, when using Chebyshev polynomial fitting double difference observations, with respect to the thoughts of robust estimation, taking into account of the order of Chebyshev polynomial fitting and the length of fitting arc, cycle slips detection and correction for single-frequency GPS data based on sliding window of robust estimation Chebyshev polynomial fitting was proposed in this dissertation. L1-frequency carrier phase data with sampling interval of60seconds and15seconds were applied for the tests, test results showed that the proposed algorithm can effectively detect multi-epoch cycle slips and continuous cycle slips, and cycle slips can be accurately repaired.5. Aiming at the problem in the conventional GPS single epoch data processing if no priori information, A new algorithm for solving GPS integer ambiguity using single epoch data was proposed in this dissertation. It uses code observation of one epoch to calculate initial ambiguity by least square method, the original search space of ambiguity was constructed by using standard deviation of the initial position, the ambiguity transformation by using two different linear combination of expansion wave was carried out to make the original search space of ambiguity smaller. After the new search space of ambiguity was confirmed, ambiguity N1and N2were solved by means of the inverse linear transformation. Furthermore, ambiguity function method was used for the searching of the true value using single epoch data. Two sets of data for different baseline length was used for analyzing and testing, the experimental results show that the proposed method was feasible and correct.6. Aiming at the problem in the conventional ambiguity algorithm of single frequency GPS kinematical positioning, a new algorithm for rapid integer ambiguity resolution was proposed in this dissertation. In the algorithm, QR decomposition transform of the coordinate coefficient matrix was adopted to eliminate the coordinate parameters in the double difference observation equation, thereby the Kalman Filter equations can be established to estimate only the ambiguity parameters. Then ordering process and double Cholesky decomposition were used for the decorrelation of the filtered ambiguities and the ambiguities were fixed by using the shrinking ambiguity search space strategy. Based on the experimental data for testing the algorithm, the analysis results show that the proposed algorithm can not only improve the accuracy of ambiguity float solution, but also has a good ambiguity decorrelation capability, and it can achieve rapid integer ambiguity resolution correctly and effectively.7. A method of GPS baseline solution based on cascade recursive without ambiguity resolution was proposed in this dissertation, considering the integer characteristic of ambiguity and the constraint condition between wavelength of carrier phase and the initial coordinate error of baseline non-reference station. The method was immune to cycle slip and it is unnecessary to take into account the ambiguity parameters in baseline solution process.The feasibility and correctness of the proposed method were demonstrated by single epoch scheme and multiple-epoch scheme with sliding window model respectively and the baseline resolution results with higher precision can be obtained.8. Using the priori information of known coordinates on reference stations, based on the combination of ultrarapid ephemeris, a three-step kalman filter algorithm for near real-time estimating tropospheric wet delay on reference stations was proposed, in the algorithm, wide lane ambiguity and pseudorange multipath error were separated by using kalman filter, and then, starting the kalman filter for separating L1ambiguity and tropospheric wet delay based on ionosphere-free combination model. After that, using the correctly fixed L1ambiguity back substitution method and rebuilding the kalman filter to estimate accurate relative tropospheric wet delay parameter, the feasibility and correctness of the algorithm was verified through numerical example. Subsequently, using near real-time tropospheric wet delay result obtained by the algorithm to calculate the corresponding near real-time precipitable water vapor, which were compared and analyzed with precipitable water vapor of GAMIT solution.