Abstract
The use of reflected Global Navigation Satellite System (GNSS) signals has shown to be effective for some remote sensing applications. In a GNSS Reflectometry (GNSS-R) system, a set of delay-Doppler maps (DDMs) related to scattered GNSS signals is formed and serves as a measurement of ocean wind speed and roughness. The design of the DDM receiver involves a trade-off between computation/communication complexity and the effectiveness of data retrieval. A fine-resolution DDM reveals more information in data retrieval while consuming more resources in terms of onboard processing and downlinking. As a result, existing missions typically use a compressed or low-resolution DDM as a data product, and a high-resolution DDM is processed for special purposes such as calibration. In this paper, a deep learning, super resolution algorithm is developed to construct a high-resolution DDM based on a low-resolution DDM. This may potentially enhance the data retrieval results with no impact on the instrument design. The proposed method is applied to process the DDM products disseminated by the Cyclone GNSS (CYGNSS) and the effectiveness of wind speed retrieval is demonstrated.
Highlights
Global Navigation Satellite System Reflectometry (GNSS-R) is a bistatic remote sensing technique in which the GNSS-R receiver acquires and processes scattered signals from the Earth’s surface that are generated by GNSS satellites
The results presented indicate that the retrieved wind speed using the SR-delay-Doppler maps (DDMs)-based data can provide as reliable of an estimation value as that obtained utilizing the fully resolved (FR)-DDM data
A preprocessing GNSS-R method for obtaining ocean surface wind speed based on the SR-DDM was proposed and validated using real Cyclone GNSS (CYGNSS) scientific data products
Summary
Global Navigation Satellite System Reflectometry (GNSS-R) is a bistatic remote sensing technique in which the GNSS-R receiver acquires and processes scattered signals from the Earth’s surface that are generated by GNSS satellites. To generate a DDM, the GNSS-R receiver performs a series of correlation processing procedures at different code phase delays and Doppler frequency bins. The National Aeronautics and Space Administration (NASA) Cyclone GNSS (CYGNSS) mission collects global surface wind field information to help predict the dynamics of hurricanes [16]. Each satellite uses four parallel channels to generate fully resolved DDMs, which contain the scattering properties above the ocean, from four Global Positioning System (GPS) satellites. The fully resolved DDM is compressed by the onboard compression algorithm to reduce the data transfer requirements. It should be noted that the compression is not a lossless algorithm
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