Precise Kinematic GPS Surveying And Quality Control

Precise kinematic GPS surveying can provide users with the precise position,velocity,attitude and time information of the moving platform in real-time or post-processing modes. It is now increasingly used for many surveying and navigation applications on land,at sea or in the air. Precise kinematic GPS surveying in single-baseline mode is investigated with the emphasis on the (near) instantaneous ambiguity resolution for short-baselines,on the ambiguitiy resolution for long-baselines and on quality control. The main achievements of this paper are as follows:1. A real-time estimation of a prior variance-covariance of GPS observations is developed for the (near) instantaneous ambiguity resolution for short-baselines,which improves the stochastic model of the observations,and then the success rate and the reliability of ambiguity resolution.2. The ionosphere-weighted model is introduced into precise kinematic GPS positioning to deal with the ionosphere over long-baselines. Further,based on the method of pre-elimination of parameters,the formulae of the partly-weigthed least squares estimation with constraints on parts of the parameters are derived to include a prior information.3. The effects of the atmosphere errors on ambiguity resolution on-the-fly are investigated for long-baselines. The results show that the ionosphere-weighted model or the tropospheric estimation,integrated with the partly-weigthed least squares,can improve,the success rate and the reliability of ambiguity resolution;However,if the ionospheric delay or the tropospheric delay,which is modeled on random walk process or first-order Gauss-Markov process,is estimated with the Kalman filter,it will reduce the success rate and the reliability of ambiguity resolution. The results also show that Saastamoinen/Niell model can remove the most of the tropospheric delay,and then significantly improve the success rate and the reliability of ambiguity resolution.4. A comparision between the partly-weigthed least squares estimation and the Kalman filter ismade on ambiguity resolution on-the-fly,which shows that the partly-weigthed least squares estimation is much better than the Kalman filter for the success rate,the reliability and the computational efficiency of ambiguity resolution.5. A cycle-slip detection and correction technique is developed to detect and correct cycle slips in dual-frequency carrier phase,named as least-squares-search method for cycle slips,which can correct almost all cycle slips when data gap is shorter than a few minutes,with the help of the geometry-free phase combination and the pseudorange minus phase linear combination.6.The effects of the atmosphere errors on the kinematic positioning solutions are assessed for long-baselines with the fixed ambiguities. The results show that Saastamoinen/Niell model can remove the most of the tropospheric delay and then significantly improve the kinematic positioning solutions;the ionosphere which is modeled on random walk process can also improve the kinematic positioning solutions;however,the troposphere which is modeled on random walk process will bias the kinematic positioning solutions.7. A comparision between the partly-weigthed least-squares estimation and the Kalman filter is made on precise kinematic GPS positioning with the fixed ambiguities,which shows that thepositioning results from the partly-weigthed least squares,which accuracy is at the level of 10 cm,are much more accurate than the results from the Kalman filter,which accuracy is at the level of a few meters.8. A general estimator for adaptively robust filter is developed,which includes the estimators of classical Kalman filter,adaptive Kalman filter,robust filter,sequential least squares (LS) adjustment and robust sequential adjustment. The procedure can not only resist the influence of outlying kinematic model errors,but also control the effects of measurement outliers.9. The precise velocity can be determined respectively with precise positioning results,receiver raw Doppler measure...