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Remote Sens. 2010, 2(10), 2426-2441; doi:10.3390/rs2102426
Article

Inferring Snow Water Equivalent for a Snow-Covered Ground Reflector Using GPS Multipath Signals

Received: 9 September 2010; in revised form: 13 October 2010 / Accepted: 18 October 2010 / Published: 20 October 2010
(This article belongs to the Special Issue Global Positioning Systems (GPS) and Applications)
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Abstract: 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° and 30°. The results from this nonlinear algorithm show potential for inferring snow water equivalent using GPS multipath signals.
Keywords: global positioning system (GPS); multipath; specular reflection; snow depth; snow density; snow water equivalent global positioning system (GPS); multipath; specular reflection; snow depth; snow density; snow water equivalent
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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MDPI and ACS Style

Jacobson, M.D. Inferring Snow Water Equivalent for a Snow-Covered Ground Reflector Using GPS Multipath Signals. Remote Sens. 2010, 2, 2426-2441.

AMA Style

Jacobson MD. Inferring Snow Water Equivalent for a Snow-Covered Ground Reflector Using GPS Multipath Signals. Remote Sensing. 2010; 2(10):2426-2441.

Chicago/Turabian Style

Jacobson, Mark D. 2010. "Inferring Snow Water Equivalent for a Snow-Covered Ground Reflector Using GPS Multipath Signals." Remote Sens. 2, no. 10: 2426-2441.


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