Journal
REMOTE SENSING
Volume 2, Issue 10, Pages 2426-2441Publisher
MDPI
DOI: 10.3390/rs2102426
Keywords
global positioning system (GPS); multipath; specular reflection; snow depth; snow density; snow water equivalent
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Funding
- Montana State University Billings' (MSUB) Research and Creative Endeavor Grant Committee
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A nonlinear least squares fitting algorithm is used to estimate both snow depth and snow density for a snow-layer above a flat ground reflector. The product of these two quantities, snow depth and density, provides an estimate of the snow water equivalent. The input to this algorithm is a simple ray model that includes a speculary reflected signal along with a direct signal. These signals are transmitted from the global positioning system satellites at 1.57542 GHz with right-hand circularly polarization. The elevation angles of interest at the GPS receiving antenna are between 5 degrees and 30 degrees. The results from this nonlinear algorithm show potential for inferring snow water equivalent using GPS multipath signals.
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