Ground-based GNSS-IR ice period detection considering residual signal-to-noise ratio characteristics

doi:10.11947/j.AGCS.2024.20230338

Abstract

Abstract:

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 detection during freezing periods has been largely unexplored, with existing methods hindered by surface property and signal variation 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 experiments using data from the Shuangwangcheng Reservoir Dam GNSS station show that the proposed method is sensitive to surface 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.

Key words: GNSS, GNSS-IR, reflected signals, ice period detection, SNR, Shuangwangcheng reservoir

CLC Number:

P227

Minfeng SONG, Xiufeng HE, Xiaolei WANG. Ground-based GNSS-IR ice period detection considering residual signal-to-noise ratio characteristics[J]. Acta Geodaetica et Cartographica Sinica, 2024, 53(12): 2295-2304.

Figures/Tables 9

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周期	L1C（0.190 3 m）		L2C（0.244 2 m）		L5（0.254 8 m）
周期		ξ		ξ		ξ
1	0.034	0.033	0.041	0.043	0.045	0.043
2	0.068	0.066	0.084	0.088	0.092	0.088