# A Novel Method for Ocean Wind Speed Detection Based on Energy Distribution of Beidou Reflections
## 1 Introduction  
As one of the most important links in the global climate system, the ocean plays a decisive role in regulating the climate through the exchange of energy with the atmosphere and water circulation. Coastal areas are threatened by storms and typhoons, especially in the northwest Pacific Ocean. Therefore, monitoring the offshore sea-state is necessary to ensure the safety of social activities in local areas. Traditional methods such as buoys and active radars have performed well in sea-state detection. However, their high cost and geographic dependence limits their quantitative distribution. The Global Navigation Satellite System Reflectometry (GNSS-R) technique has been an innovative option for remote sensing since it was first proposed for mesoscale altimetry by [PERSON] in 1993 [1]. This technique exploits signals of opportunity from GPS or other GNSS constellations (Galileo, Beidou, Glonass, etc.) being reflected off the Earth's surface to retrieve various geophysical parameters of the Earth's surface. During the initial period, scientists mainly focused on GNSS-R based ocean remote sensing, such as sea altimetry and scattermetry [1; 2; 3; 4; 5; 6; 7; 8]. During the last two decades, the applications of the GNSS-R technique have expanded to various fields, such as monitoring of sea-ice, sea salinity, snow depth, oil spilling and soil moisture [9; 10; 11; 12; 13]. Meanwhile, various experimental activities have been performed to demonstrate the performance of this technique. A detailed review of GNSS-R principles, applications and future space-borne missions can be found in [14; 15]. Among others, sea surface wind speed measurement has been one of the most important applications of the GNSS-R technique. Through processing data from an airborne experiment, ocean wind measurement based on GPS reflections was first presented in [5]. Since then, several algorithms and observables have been proposed to retrieve sea surface wind speed and sea state in different experimental scenarios, including ground-borne, air-borne and space-borne [16; 17; 18; 19; 20; 21; 22]. Among them, some observables are proposed to develop empirical wind retrieval models, which are defined as the descriptors of \"size\" or \"shape\" of 1-D delay waveforms or 2-D delay-Doppler maps (DDM) such as DDM area and volume within a given threshold [18; 23; 24]. These observables perform well for wind speed retrieval both in airborne and space-borne experiment scenarios. Nevertheless, these observables do not perform well in low altitude experience scenarios due to the limited extension of the glistening zone [14]. By considering the coherent and incoherent component of the received signal, some other observables such as coherent time and effectiveness of incoherent averaging are proposed and related to the significant wave height (SWH) [6; 20; 25]. When the specular component is dominant in the scattering process, these observables perform well in low altitude platform, especially in ground-based scenarios. In [26], the delay-related and spectral-related observables, defined as relative-amplitude and Doppler centroid, respectively, are proposed for typhoon wind retrieval. In [27], the ratio between coherent and incoherent components was discussed for coastal wind retrieval. Beidou consists of a hybrid constellation with the satellites in different orbits, including the inclined geosynchronous satellite orbit (IGSO), the geostationary earth orbit (GEO) and the medium earth orbit (MEO). Until now, with 22 satellites in-orbit, Beidou has provided integrated position, velocity and time (PVT) services in Asia-Pacific regions. Therefore, a mass of reflections over the sea surface from Beidou satellites can be used for remote sensing. In [28], an exponential empirical model for monitoring wind speed was established based on the coherent time of Beidou reflections. In addition, researchers also demonstrated the feasibility of ocean altimetry, employing reflected Beidou signals in [29].