Suppressing stationary dominant reflectors in GNSS-R imaging via repeat-pass modeling and ECA-B

Abstract Imaging based on signals reflected from global navigation satellite systems (GNSS) represents a novel approach for surface observation. Owing to the global coverage of navigation satellite constellations and the short revisit periods of satellite sub-points, GNSS reflectometry imaging enables high-temporal-resolution change detection in sensitive areas. However, stationary dominant reflectors (SDRs) in the imaging area suppress the signal amplitudes of nearby weak reflection targets, thereby increasing the difficulty of their detection. Conventional coherent change detection and differential interferometry methods demand high phase accuracy and require multiple imaging operations within the imaging domain, thereby reducing detection efficiency. To address these issues, this study proposes a method for directly suppressing SDRs directly in the range-compressed domain. This method leverages the extensive cancellation algorithm batches (ECA-B) framework and utilizes a single satellite revisit period to construct a scattering characteristic model dominated by SDRs, which serves as the reference signal for ECA-B cancellation. To ensure model stability, two-dimensional range-compressed results from multiple prior revisit periods were accumulated to construct a weighted scattering characteristic model, incorporating noise mean and variance. Simulations and real-world experiments demonstrated that the proposed method significantly attenuates signals from strong reflectors in the range-compressed domain, thereby enhancing the detectability of weak change targets.