2026· IEEE Geoscience and Remote Sensing Letters· Vol 23, pp. 4013205-4013205· 0 citations· 12 references
Abstract
Existing GNSS-reflectometry interferometric synthetic aperture radar (GNSS-R InSAR) elevation deformation monitoring methods derive interferometric phases from SAR images, causing measurement intervals to be constrained by the synthetic aperture duration and limiting their ability to capture rapid deformation. To overcome this limitation, this letter proposes a high-temporal-resolution GNSS-R InSAR method using range-compressed phases. Once the target location has been determined through initial SAR imaging, the proposed method directly extracts range-compressed phases from each azimuth sample for elevation deformation retrieval without repeated SAR imaging. The projection stability and phase-noise characteristics associated with range-compressed phase extraction are analyzed, and corresponding filtering strategies are employed for noise suppression. Experiments at a 0.4s validation interval demonstrate that, after filtering, subcentimeter elevation deformation retrieval accuracy can be achieved, with correlation coefficients (CCs) exceeding 0.97 under different satellite observation geometries. Compared with conventional GNSS-R InSAR approaches, the proposed method significantly improves temporal resolution, with a theoretically achievable native phase-update interval of approximately 1 ms.
Global Navigation Satellite System (GNSS)-based interferometric bistatic synthetic aperture radar (InBSAR) enables deformation monitoring using on-orbit navigation satellites as transmitters and a ground-fixed receiver. However, the low spatial resolution, poor signal-to-noise ratio (SNR), and inherent asymmetric bista...
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Interferometric Synthetic Aperture Radar (InSAR) deformation measurements are susceptible to long wavelength errors, yet existing geometric and strain models for estimating three-dimensional (3D) deformation from combined Global Navigation Satellite System (GNSS) and InSAR observations do not explicitly account for t...
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Bridge parameter inversion from synthetic aperture radar (SAR) data has traditionally relied on fully polarimetric (FP) observations, where $\mathrm {Re}(\langle S_{HH} S_{VV}^{*}\rangle)$ is used to localize double-bounce scattering stripes. This letter demonstrates, for the first time, the feasibility of bridge multi...
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