Ground GNSS Remote Sensing For Near-surface Water Environmental Parameters

The expansion of research and application of the global navigation satellite systems(GNSS)has revealed inherent information.The Zenith Total Delay(ZTD)caused by atmospheric refraction and multipath error caused by multipath phenomenon were thought to be two important errors in positioning using GNSS.However,the refracted and reflected signals carry characteristic information of medium.For example,GNSS radio navigation signals reflected from a surface carry characteristic information of the reflecting surface(including sea level,snow depth,soil moisture,et al.);and the ZTD values could carry information of the atmospheric water vapor.The goal of this dissertation is to develop the technique of GNSS reflectometry(GNSS-R)for ground-based measurement of water cycle.The main contents and achievements of this dissertation are as follows.1.The research status of ground-based GNSS remote sensing is summarized and the principles of ground-based GNSS water vapor retrieval and GNSS-IR are studied.Also,the significance of near-earth space water environmental parameter monitoring is analyzed.2.In order to research the spatial and the temporal characteristic of the Precipitable Water Vapor(PWV),the data of Global Positioning System(GPS)stations at Taiwan are chosen to analyze.The long and the short time series of GPS water vapor for Taiwan are decomposed by Empirical Mode Decomposition(EMD)and Wavelet Decomposition(WD).Then the periodic oscillation characteristics of water vapor time series and the physical causes of different periodic oscillations are studied.This dissertation also studies a typical frontal rainfall in Taiwan by analyzing the changed characteristics of the meteorological elements before and after the rain retrieved from ECMWF and GPS.3.According to the classical principles of GPS-IR,the soil moisture,snow parameter and sea level are simulated and are estimated.The mathematical relationship between the SNR characteristic parameter and the environmental parameter can be established from the simulation analysis.Then the soil moisture,snow parameter and tide level are estimated by the classical GPS-IR method following this mathematical relationship.The results show a good correspondence between the measured environmental parameter series and the retrieval series.4.There are two important corrections in the process of sea level retrieval by GNSS-IR using geodetic-quality receiver,called tropospheric correction and dynamic correction.The bias caused by atmospheric refraction effect at different elevation angles is analyzed,and the atmospheric refraction correction formula is used for tropospheric correction.Also,the dynamic formulas considering the dynamic change of the reflecting surface are deduced.Two kinds of dynamic correction algorithms,named classical correction algorithm and dynamic algorithm,are improved.The innovation points of this dissertation are as follows.1.Considering the effect of terrain fluctuation in snow depth retrieval by GPS-IR,the theory and method of planarization of snow depth retrieval using Grid model is proposed to select the reflector height values of the horizontal reflecting zone in this grid model.This method to discover the anisotropic information hidden in SNR series can provide plane information of environmental parameters,and can correct the bias of snow depth retrieval caused by terrain fluctuation.2.Considering the errors caused by noise in sea level estimation,a data processing method using wavelet decomposition theory is proposed to remove noise signals in SNR series.It can reduce the frequency energy of noise in LSP spectrum diagram and can avoid the appearance of false frequency peaks,leading a snow depth retrieval result with less gross error.3.In order to improve the accuracy and the resolution of the sea level retrieval,a fusion algorithm for sea level retrieval based on GNSS multi-mode multi-frequency SNR data is proposed.The algorithm based on the clustering idea,the sliding window algorithm and the least squares solution,achieves the the retrieval results with accuracy less than 20 cm in a time resolution of 1 h,balancing the contradiction between accuracy and resolution well.This fusion algorithm is of great significance for advancing the application process of GNSS-IR for sea level retrieval.4.In order to improve the resolution of the sea level retrieval,the wavelet analysis method is used to extract the instantaneous frequency information in SNR.Then a method using this instantaneous frequency for sea level retrieval is proposed.The results show that when the quality of the SNR sequence is good,the wavelet analysis can greatly increase the number of retrieval with less and even no loss of precision.This sea level retrieval method using instantaneous frequency aims to discover the more information hidden in SNR series,improving the effective utilization of SNR data.