Research Application Of Snow Depth Detection Method Based On GNSS-R Technology

With the development of GNSS applications,GNSS-R?Global Navigation Satellite System Reflectometry?technology based on the GNSS signal-to-noise ratio emerged at the historic moment.GNSS-R technology is an emerging technology that uses navigation satellite system multipath reflection signals for remote sensing of the sea or land surface.This technology can mine all kinds of surface information contained in the reflection signals.Snow cover is a very active natural element on the surface,and it is also an essential factor influencing the water cycle and climate regulation.The general snow depth detection method is weak in time and space and cannot achieve long-term continuous large-scale accurate measurement of snow depth,while satellite remote sensing tends to detect snow cover in a range other than depth.In order to improve the current shortcomings,this study intends to use GNSS-R technology to identify snow depth with excellent spatial and temporal continuity.Experimental research on inversion.This article combines the research results of scholars at home and abroad in recent years,starting from the basic characteristics of GNSS reflected signals,to clarify the multi-path mathematical model and the signal-to-noise ratio relationship and GNSS-R technical principles.The observation data of the Altay Chonghuer?ALCH?station at the Xinjiang provincial CORS station was selected to conduct a single-star GNSS-R technical surface snow depth inversion study.The deviation between the experimental inversion value and the measured value is±10cm,and the result is not satisfactory.To this end,this paper proposes multi-star multi-system data,high-quality control methods,and inversion experiments,using correlation coefficients,root mean square error,average deviation,and other indicators to discuss its accuracy influencing factors,the optimal experimental results and measured The correlation coefficient of snow depth change is 0.9910.The average deviation is 1.095cm,which reflects the change of snow depth in a long time series,and realizes the inversion of surface snow depth in the Altay region of Xinjiang based on GNSS-R technology of CORS system.The main content and results of this article are as follows:1.By combing the multipath error and signal-noise ratio?SNR?related characteristics and their influencing factors,We have obtained a linear relationship between the multi-path reflected signal and the direct signal phase difference and the sine or cosine value of the height angle.The random signal changes lead to the instability of the phase and amplitude of the straight and reflected mixed signals,which causes the SNR sequence to oscillate and decrease in value.It provides a theoretical basis for subsequent research.2.Through the Fresnel reflection area,the signal reflection point trajectory selects the SNR sequence.We use the LSP?Lomb-Scargle periodogram?spectrum analysis method to calculate the SNR residual sequence of non-equally-sampling sampling.This method can extract the weak periodic signal,and it can weaken the false spectral peaks generated,and provide a method guarantee for the data processing of GNSS-R technology snow depth detection.3.Using the original observation data of GNSS at the ALCH station,the process of obtaining an SNR residual sequence by different strategies such as removing the SNR trend term and unit linearization is discussed in detail.We use the GPS,BDS,GLONASS three navigation satellite systems respectively.With the different satellite number,different time scale reflection signal to invert snow depth experimental research,combined with the measured snow depth data,GPS,BDS,GLONASS satellite system inversion value and measured value The correlation coefficients r are0.9850,0.9781,and 0.9573,respectively.4.Use GPS L1,L2,L5 signals,Beidou system B1,B2 signals,GLONASS system R1,R2 signals,namely SNR_{L1,L2,L5,B1,B2,R1,R2}sequence,multi-frequency multi-mode GNSS-R technology Snow depth inversion.The accuracy of the satellite is analyzed from four aspects:altitude angle,constellation structure,signal frequency,and data sampling rate.The results show that the difference in the data sampling rate will not cause a significant difference in the results.The satellite altitude angle range is 5°?25°,and the multi-system multi-satellite multi-frequency inversion is the best with an accuracy of±2cm.5.Using the ALAL,ALCH,and ALJM observation data of three sites distributed in a triangle network in the Altay area,the long-term snow depth change inversion was performed.The experimental results were in agreement with the actual data reported by Altay Meteorological Bureau.This study realized continuous and large-scale snow depth change monitoring in the northwest of Altay.It was forming snow data with good spatiotemporal continuity,providing a strong basis for SNR-based GNSS-R technology to monitor surface environmental parameters,with a view to the future of GNSS-R technology.It can be applied in the field of meteorological monitoring.