基于Kalman滤波的GPS水汽层析方法及其应用

Method of GPS Water Vapor Tomography Based on Kalman Filter and Its Application

开发了基于Kalman滤波的GPS水汽层析方法,Kalman滤波提供了一种高效可计算的方法来估计过程的状态。将这种方法应用于海南地区GPS小网观测试验中,成功地层析出观测站上空大气水汽的垂直结构。结果表明,GPS层析得到的水汽廓线信息与探空符合较好,即使水汽先验估计存在±50%偏差的情况下,依然能获取正确、可靠的水汽垂直结构信息。通过初步分析认为,层析结果较稳定的原因可能是因为这种方法在一定程度上避免了层析方程解算过程中的病态问题,且对水汽先验信息并不敏感,使得层析结果更忠实于原始GPS观测资料。

A tomography method based on Kalman filter was developed.Kalman filter method is an efficient filter that is easily computed and able to estimate the state of a system from a series of measurements.This method is tested in a small GPS network experiment performed in Hainan region and water vapor vertical structure above GPS sites is successfully obtained.The results show that tomographic water vapor vertical profiles agree well with profiles from radiosondes.Kalman filter tomography can retrieve correct and reliable water vapor vertical structure even on the situation of a priori information containing ±50% bias.Analysing the reason of stable results,it is may be that this method avoids the ill-posed problems of tomographic equations to some degree,and is insensitive to a priori information of water vapor.Therefore,the tomographic results even more depend on raw GPS observation data.