GPS蒙特卡罗三维水汽层析算法敏感性试验和研究

以布设在天津的由13部地基GPS组成的高密度小尺度探测网为基础, 对蒙特卡罗层析算法中GPS平均站距、层析时间间隔以及蒙特卡罗随机次数3个影响层析算法的关键参数进行敏感性实验和分析。实验表明, 层析解算精度随着平均站距的降低和蒙特卡罗次数的增加而提高, 增加层析时间间隔对提高层析算法结果的精度作用不明显。同时提出采用“最优+次优”的两组残差最小水汽场的平均作为最终层析场的方法, 使得水汽场绝对偏差较前人所采用的只取残差最小水汽场的方法减少约30%。

Sensitivity Experiment of Monte Carlo Tomography Algorithm of Water Vapor Using GPS Data

The data of the network of 13 GPS are used to perform the sensitivity tests for the important parameters of the Monte Carlo tomography algorithm such as the average distance of the GPS stations, tomography temporal resolution and Monte Carlo random times. The accuracy of tomography rises with the decrease of the average station distance and the increase of the random times. However the decrease of the temporal resolution of the tomography does not help much to the accuracy of the tomography. A new way is also proposed to obtain the final tomography field. The final tomography field is obtained by averaging “sub-optimal” tomography fields instead of the one “optimal”, and it is proved to reduce the error by around 30%.