Ground-Based Differential Interferometry SAR: A Review

Wang, Yanping; Yang, Song; Hong, Wen; Zhang, Yuan; Lin, Yun; Yang, Li; Bai, Zhaoguang; Zhang, Qiming; Lv, Sen; Liu, Hang

doi:10.1109/mgrs.2019.2963169

Cited by 54 publications

(25 citation statements)

References 73 publications

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“…Its common center frequency is 17.5GHz and the bandwidth is often set to 1GHz. According to the existing NCUT-ArcSAR parameters, the rotating arm length L is set to 1m [32]. The phase center distribution rsn is the parameter of circular GBSAR with optimal sparse spectrum distribution, and rcn is the parameter of circular GBSAR with continuous spectrum distribution.…”

Section: Simulationsmentioning

confidence: 99%

Multi-Phase-Center Sidelobe Suppression Method for Circular GBSAR Based on Sparse Spectrum

et al. 2020

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Circular ground-based synthetic aperture radar (GBSAR) is a new type of GBSAR with three-dimensional (3D) imaging capability. Its relatively low bandwidth-to-frequency ratio and donut shaped spectrum cause high sidelobes problem, which seriously affects the quality of SAR images. To solve this problem, a multi-phase-center sidelobe suppression method for circular GBSAR based on sparse spectrum is proposed in this paper. This method optimizes the sparse spectrum distribution of multi-phasecenter circular GBSAR to suppress the originally high sidelobes. In this paper, the signal model of multiphase-center circular GBSAR is established, the point spread function (PSF) is derived, and the relationship between the sparse spectrum distribution and the sidelobe level is also analyzed. Moreover, we provide the optimal distribution of the sparse spectrum, thus the optimal distribution of multiple phase centers can be calculated with given imaging geometry, providing the best sidelobe performance. The proposed method is verified via simulation experiments.

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Section: Simulationsmentioning

confidence: 99%

Multi-Phase-Center Sidelobe Suppression Method for Circular GBSAR Based on Sparse Spectrum

et al. 2020

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“…Among the latter, Ground-Based Synthetic Aperture Radars (GBSAR) achieved success as remote sensing tools for environmental monitoring. GBSAR sensors allow to scan the desired scenario and detect possible displacements of targets in the radar line of sight [3], [4]. The use of interferometric techniques permits to measure targets displacement with an accuracy of a fraction of the signal wavelength.…”

Section: Introductionmentioning

confidence: 99%

Kalman Filter Application to GBSAR Interferometry for Slope Monitoring

2022

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The use of Kalman filtering techniques for landslide monitoring has proved effective as a tool for estimating and predicting land displacements. Ground-Based Synthetic Aperture Radars (GBSAR) are popular remote sensing instruments able to provide displacement maps of the investigated area, with submillimeter precision. These instruments outperform other sensors in several respects, such as all-weather and all-day monitoring. However, in some cases, for instance in vegetated scenarios, the displacement is affected by a significant uncertainty due to the decorrelation of the radar signal. In such a case, to retrieve any reliable information, noise must be filtered out using appropriate methods. Given the success of kinematic modeling of landslide movements through Kalman filtering, this technique seems to be the optimal candidate for processing the displacement measured by interferometric GBSAR data. This paper investigates this idea, by applying Kalman Filter to GBSAR measurements acquired in two different campaigns: a landslide monitoring in north Spain, and a sliding glacier monitoring in the Alpes, Italy. A proper initialization of the algorithm parameters is fundamental for a correct application of the Kalman filter. In this work, we present a strategy that exploits information from coherent pixels for tuning the filtering parameters and optimizing the filter performance on areas with low coherence.

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“…Ground-Based Synthetic Aperture Radar (GBSAR) [1] interferometry is a powerful tool that enables the measurement of target displacements with sub-wavelength precision. This popular technique is currently applied for monitoring natural and urban scenarios.…”

Section: Introductionmentioning

confidence: 99%

Temporal Coherence Estimators for GBSAR

Beni

Miccinesi²,

Michelini³

et al. 2022

Remote Sensing

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Many Ground-Based Synthetic Aperture Radar (GBSAR) applications demand preliminary analysis to select areas with high-quality signal. That is, areas in which the phase can be processed to extract the desired information. The interferometric coherence and the amplitude dispersion index are important tools widely used in the literature to assess the quality of GBSAR images. So far, no direct relation has been found between the two. Indeed, they are parameters of different natures: amplitude dispersion index is calculated with only amplitude values, while coherence provides information also on the signal phase. The purpose of this article is to find a relation between the two parameters. Indeed, the amplitude dispersion index provides some practical advantages if compared to coherence estimators, especially to perform fast preliminary analysis. In this article, a theoretical relation between amplitude dispersion index and coherence is retrieved. GBSAR measurements acquired in different scenarios, at different working frequencies are presented and used to validate such a relation.

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Ground-Based Differential Interferometry SAR: A Review

Cited by 54 publications

References 73 publications

Multi-Phase-Center Sidelobe Suppression Method for Circular GBSAR Based on Sparse Spectrum

Multi-Phase-Center Sidelobe Suppression Method for Circular GBSAR Based on Sparse Spectrum

Kalman Filter Application to GBSAR Interferometry for Slope Monitoring

Temporal Coherence Estimators for GBSAR

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