GNSS-IR For Snow Depth Retrievals And Software Design

Snow is an indispensable part of the hydrological cycle,and an important reserve of fresh water resources in the world.Accurate determination of snow parameters is of great significance for snow disaster monitoring,climate change analysis,agricultural production and other aspects.With the continuous improvement of GNSS and the continuous expansion of application fields,GNSS has performed well in traditional applications,including positioning and navigation,speed measurement,and timing.At the same time,it is found that the reflected signal of GNSS can also be received and utilized.The method is to receive and process the GNSS signal from the reflected surface for extract the physical characteristics of the reflected surface,which becomes a new type of remote sensing technology,called GNSS-IR(GNSS Interferometric Reflectometry).GNSS-IR technology has played a significant role in snow depth retrievals with its advantages of low cost,high temporal and spatial resolution,and multiple signal sources.First,this article explained the basic principles and methods of GNSSIR technology for snow depth retrievals based on SNR and geometry-free linear combinations of carrier phase,and analyzed the accuracy of snow depth retrievals through actual GNSS observations;Then,the effectiveness of the universal GNSS receiver for monitoring the surface environment was verified;Finally,the snow depth retrievals software based on GNSS-IR technology in MATLAB environment was implemented to promote the application of GNSSIR technology faster and better.The main research contents and results of this paper are as follows:1.The basic principle and detailed process of GNSS-IR technology for snow depth retrievals based on signal to noise ratio(SNR)and carrier phase observations are introduced in detail.In addition,the effectiveness and reliability of GNSS-IR technology in snow depth retrievals have been verified based on GNSS stations form PBO(Plate Boundary Observatory)and GEONET(GPS Earth Observation Network)networks.Aiming at the problem of abnormal value in snow depth retrievals,neural network is used for quality control.Preliminary experimental results show that it can effectively reduce the impact of environmental interference.2.From the quality of observation data,the number of effective arcs,and the accuracy of reflector height retrievals,the performance of universal GNSS receiver for monitoring the surface environmental parameters was analyzed,based on the co-located universal and geodetic GNSS stations.It is hoped that GNSS-IR technology can be applied in practice faster.3.The snow depth retrievals software based on GNSS-IR technology in MATLAB environment was realized.The software provides functions including checking data quality,drawing of reflection point trajectories and the Fresnel zone,displaying reflected signals and spectral analysis results,and displaying snow depth retrievals based on SNR or carrier phase observations in time domain and spatial domain.The software was tested with actual GNSS observation data.The results show that the GNSS-IR snow depth retrievals software can comprehensively process GNSS observation data and obtain robust and effective results.