Abstract This paper introduces CEEMDAN to replace the commonly used quadratic polynomial method to decompose the original signal-to-noise ratio signal, directly extract the corresponding intrinsic mode function, and then use GNSS-MR technology to retrieve snow depth. Experiments with Colorado NWOT station GPS data show that, compared with the traditional method, the root mean square error of this method is decreased by 30.7% and the correlation coefficient with actual snow depth is 0.965, which verifies the effectiveness of the method in this article.
Key words :
GNSS-MR
CEEMDAN
multipath effect
snow depth
Cite this article:
XUE Zhangfang,LIU Lilong,WU Haojian et al. GNSS-MR Snow Depth Inversion Based on CEEMDAN[J]. jgg, 2022, 42(1): 25-28.
XUE Zhangfang,LIU Lilong,WU Haojian et al. GNSS-MR Snow Depth Inversion Based on CEEMDAN[J]. jgg, 2022, 42(1): 25-28.
URL:
http://www.jgg09.com/EN/ OR http://www.jgg09.com/EN/Y2022/V42/I1/25
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