Ground-based GNSS-IR ice period detection considering residual signal-to-noise ratio characteristics
The GNSS interferometry reflectometry(GNSS-IR)is a promising technique for retrieving land and ocean surface parameters due to its cost-effectiveness and high sampling resolution.Despite its potential,GNSS-IR's application in ice detec-tion during freezing periods has been largely unexplored,with existing methods hindered by surface property and signal varia-tion effects.This paper addresses these challenges by examining the differences in reflected signals from ice and water through modeling and simulation based on dielectric constants and surface roughness.We introduce a novel ice detection method using the power factor parameter,derived from the envelope integration of residual signal-to-noise ratio(SNR).Validation experi-ments using data from the Shuangwangcheng Reservoir Dam GNSS station show that the proposed method is sensitive to sur-face dielectric properties,roughness,frequency,and ice thickness.The power factor method demonstrates effectiveness and robustness across BDS and GPS data for all frequency bands,offering a reliable approach for ice detection that enhances GNSS reflectometry technology's monitoring capabilities.
GNSSGNSS-IRreflected signalsice period detectionSNRShuangwangcheng reservoir
万方数据
维普
