High-resolution ocean waves are significant for safe navigation and marine disaster monitoring. Hence, a methodology for dynamically monitoring the significant wave height (SWH) of the sea surface using the reflected signal from BeiDou satellites is proposed in this paper. The approach involves employing observables containing elevation and azimuth angles to establish a bivariate field for retrieving SWH, thereby effectively accounting for the coupling among observables induced by variations in observation geometry. In this paper, a receiver for real-time processing of direct signal and reflected signal was carried on shipborne platform. The results of the processing are clearly displayed by delay-Doppler maps (DDMs). According to the dependency of the DDM observables on SWH, two observables average signal to noise ratio (ASNR) and time delay window (TDW) are extracted from the generated DDM. Dimensionality reduction and reconstruction are employed in the joint processing of the observables, leading to the establishment of a bivariate correction (BVC) model for retrieving the SWH. Finally, the performance of the proposed BVC model is compared to a single-variable approach, using ERA5 and WAVERYS as reference datasets, and further validated with synchronous satellite altimeter SWH measurements as an independent observation. The inversion results of the experimental route indicate that the minimum root mean square errors (RMSE) of the ERA5 and WAVERYS are 0.167 m and 0.201 m, respectively, and shows overall consistency with the satellite altimeter observations. This work achieves high-resolution monitoring of SWH and provides significant inversion performance. • A novel shipborne GNSS-R methodology using BeiDou reflected signals is developed for high-resolution and real-time significant wave height monitoring. • A bivariate correction model that integrates ASNR and TDW observables through dimensionality reduction and reconstruction significantly enhances inversion accuracy. • Field validation demonstrates high retrieval performance, achieving minimum RMSE values of 0.167 m (ERA5) and 0.201 m (WAVERYS), outperforming single-variable approaches.
Bai et al. (Wed,) studied this question.