GNSS水汽层析的约束条件方程变权代数重构算法

基于传统代数重构算法（algebraic reconstruction technique, ART）提出一种约束条件方程变权的代数重构算法(variable weight algebraic reconstruction technique, VWART)，利用2019-08香港地区CORS网GNSS观测数据进行实验，选用京士柏探空气象站探空数据进行验证分析。结果表明，相比于传统代数重构算法，变权代数重构算法的精度、稳定性和可靠性均有所提高。以探空数据为例，其RMSE降低20.334%；在不同程度降水条件下，变权代数重构算法反演的垂直水汽廓线分布均优于传统代数重构算法。

Algebraic Reconstruction Techniques with Variable Weight of Constraints for GNSS Water Vapor Tomography

Based on the traditional algebraic reconstruction technique (ART), an variable weight algebraic reconstruction technique (VWART) of constraint equations is proposed, and the GNSS observation data of CORS network in Hong Kong area in August 2019 is used for experiments, and the sounding data of HKKP is selected for verification and analysis. The results show that, compared with the traditional ART, the accuracy, stability and reliability of the solution results of the VWART are improved. The RMSE is reduced by 20.334% using the sounding data as an example, and the vertical water vapor profile distribution of the VWART is better than that of the traditional ART under different levels of precipitation.