Research On Methods Of GNSS-IR Sea Level Estimation Based On Combination Of Observations

Monitoring and researching sea level changes are important for the natural environment,social-economics and ecosystem of coastal areas.The traditional methods of sea level monitoring include satellite altimetry and tide gauge observe technique,among which satellite altimetry data have low accuracy in coastal areas and tide gauge data are vulnerable to factors such as crustal subsidence.With the development of the Global Navigation Satellite System(GNSS),the observation of sea level using the interference phenomenon between the reflected and direct signals in coastal GNSS receivers has become a new technical means,namely GNSS interferometric reflectometry(GNSS-IR),which can use conventional geodetic receivers,with simple deployment and low cost,and can make use of the rich data sources provided by the coastal Continuously Operating Reference System(CORS)stations.The current inversion of sea level estimation using GNSS-IR technology is mainly based on SNR observations,but considering that there are cases of unrecorded SNR in early receivers,this makes it meaningful to study the inversion of sea level using combinations of multi-frequency observations or combinations between code pseudorange and carrier phase observations to replace SNR data,which can increase the diversity of sea level inversion methods.Therefore,this paper focuses on the GNSS-IR sea level inversion method with multi-frequency observation combination and code pseudorange and carrier phase observations combination.The main research contents of the paper include:(1)The overview of each GNSS satellite system involved in GNSS-IR and the signal composition of each system at different frequencies are introduced in detail.The GNSS-IR principle is introduced in conjunction with the polarization characteristics of the signal in the propagation process.(2)A method of sea level inversion based on signal-to-noise ratio(SNR)observations is implemented,and a dynamic sea level calculation method based on sliding window and robust regression is cited,which can effectively improve the spatial and temporal resolution of sea level inversion and the accuracy of dynamic sea level inversion.The method is validated using SNR data from coastal tide gauge,and the results show that the dynamic sea level RMSE by inversing are improved by 3-6 cm compared with those of the tide gauge data.(3)In order to improve the accuracy of single-frequency SNR inversions,a peak-weighting method is introduced,i.e.,the peak value of Lomb-Scargle Periodogram(LSP)spectral analysis is used as the weight to fuse the inversion results of GPS two-frequency observations.Based on the measured GPS SNR data from coastal stations,the accuracy of the method is verified,and the results show that the accuracy of the combined dual-frequency inversion using peak weighting is better than that of the GPS single-frequency inversion under good sea conditions,but the accuracy improvement is not obvious when the sea surface is rough.(4)The GNSS-IR altimetry method of observation combination is proposed,including multi-frequency observation combination(dual-frequency code pseudorange combination,triple-frequency code pseudorange combination,dual-frequency carrier phase combination,triple-frequency carrier phase combination)and code pseudorange and carrier observation combination(single-frequency code pseudorange and single-frequency carrier phase combination,single-frequency code pseudorange and dual-frequency carrier phase combination,Melbourne-Wubbena(M-W)combination).The results show that the inversion results obtained by these methods are in good agreement with the measured sea level at the tide gauge,and the RMSE can reach the decimeter level,and the correlation coefficients of the two stations are better than 0.88 and 0.72 respectively,which can achieve the same accuracy of sea level inversion as the SNR method.