Abstract

Reflected GNSS signals offer a great opportunity for detecting and monitoring of water level variation, land surface roughness and the atmosphere around the Earth. The application type intensely depends on satellites’ geometry and the topography of study area. GNSS-R can be used in sounding the water vapor as one of the most important parameters in troposphere. In view of temporal and spatial changes, retrieval of this parameter is complicated. GNSS tomography is a common approach for this purpose. Considering the dependency of this inverse approach to the number of stations and satellites’ coverage at study area, tomographic reconstruction of water vapor is an ill-posed problem. Additional constraints are usually used to find a solution. In this research reflected signals known as GNSS-R are offered for the first time to resolve the rank deficiency of this problem. This has been implemented to a tomographic model which has been already developed for modeling the water vapor in the North West of Iran. In view of low number of GPS stations in this area, the design matrix of the model is rank deficient. Simulated results demonstrate that the rank deficiency of this matrix can be reduced by implementing appropriate number of GNSS-R stations when the spatial resolution of model is optimized. Resolution matrix is used as a measure for analyzing the efficiency of the proposed method. Results from DOY 300 and 301 in year 2011 show that the applied method can even remedy the rank deficiency of the design matrix. The satellites’ constellation and the time response of the model are the effective parameters in this respect. On average the rank deficiency of the design matrix is improved more than 90% when the reflected signals are used. This is easily seen in terms of the resolution matrix of the model. Here, the mean bias and RMSE of reconstructed image are 0.2593 and 1.847 ppm, respectively.

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