A Multiple Eigenvalues-based Approach for Spaceborne GNSS-R Sea Surface Wind Speed Inversion

The wind speed is an important parameter to describe the sea state, but the tools of observing the sea surface wind speed are limited at present. Satellite-borne observation which is based on Global Navigation Satellite System Reflectometry (GNSS-R) provides a new method for obtaining global wind field information. GNSS-R sea surface wind speed detection technology has the characteristics of all-day operation, low power consumption, wide coverage, multi-signal source, low cost, etc., which complements other wind measurement technologies and makes up for the shortcomings of other wind measurement methods, and has been widely concerned. The study of Delay-Doppler Map (DDM) of GNSS sea surface scattered signals is very important for the inversion of sea surface wind speed. In this paper, the steps of DDM simulation are briefly introduced, and the effects of wind speed, satellite altitude, satellite incidence angle and other important parameters on DDM are investigated. Then, the method of retrieving sea surface wind speed using ocean reflected signal of GNSS is studied. By analyzing the impact of incident angle and wind speed on DDM, we find that there are some specific delay areas in which the incident angle has less impact on DDM, and calculate the eigenvalues of these areas. In order to improve the accuracy of wind speed inversion, the sensitivity of multiple eigenvalues (such as peak value, trailing-edge slope, leading-edge slope, delay window length, etc.) to wind speed is discussed. The appropriate characteristic values are found via the comparison of above sensitivities, and a more accurate method of wind speed inversion is finally achieved by performing wind speed inversion at different incident angles based on these eigenvalues.