GPS参考站对流层湿延迟近实时估计的三步滤波算法

A Three-step Kalman Filter Algorithm for Near Real-time Estimating Tropospheric Wet Delay on GPS Reference Stations

利用参考站坐标已知的先验信息,基于组合后的超快星历,提出了一种参考站对流层湿延迟近实时估计的三步Kalman滤波算法,该方法先利用Kalman滤波分离宽巷模糊度与伪距多路径误差,再基于电离层无关组合模型,启动Kalman滤波器进行L1模糊度与相对对流层湿延迟的分离,然后利用将正确固定的L1双差模糊度进行回代的方法,重新构建Kalman滤波器来估计准确的相对对流层湿延迟参数,通过实例验证了该方法的可行性和正确性。

Using priori information from known coordinates for reference stations,based on tacombination of ultrarapid ephemeris,a three-step kalman filter algorithm for near real-time estimation of tropospheric wet delay on reference stations is proposed.In this algorithm,wide lane ambiguity and pseudorange multipath error are separated by using a Kalman filter,and then,using the Kalman filter for separating L1 ambiguity and tropospheric wet delay based on na ionosphere-free combination model.After that estimating an accurate relative tropospheric wet delay parameter using the correctly fixed L1 ambiguity back substitution method and rebuilding the Kalman filter.The feasibility and accuracy of the algorithm is verified through numerical examples.