Bibliographies: 'Ground-Based Synthetic Aperture Radar (GBSAR)'

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Lim, Chee Siong, Voon Chet Koo, and Yee Kit Chan. "The Integrated Simulation and Processing Tool for Ground Based Synthetic Aperture Radar (GBSAR)." Journal of Engineering Technology and Applied Physics 1, no. 2 (2019): 20–24. http://dx.doi.org/10.33093/jetap.2019.1.2.5.

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Ground-based Synthetic Aperture Radar (GBSAR) is a tremendous example of the extended applications of Synthetic Aperture Radar (SAR). GBSAR is extremely useful in human-made structure observations, terrain mapping, landslide monitoring and many more. However, the process of designing and developing the GBSAR system is rather costly and time-consuming. It would be of a great advantage for system designers to have a realistic simulation and designing tool to anticipate the results before the implementation of the final design. In this paper, we are going to present the integrated simulation and designing tool that we have developed for a generic GBSAR system. We named it iSIM v2.0.

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Siong Lim, Chee, Voon Chet Koo, and Yee Kit Chan. "The Integrated Simulation and Processing Tool for Ground Based Synthetic Aperture Radar (GBSAR)." Journal of Engineering Technology and Applied Physics 1, no. 2 (2019): 20–24. http://dx.doi.org/10.33093/jetap.2019.1.2.50.

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Abstract:

Ground-based Synthetic Aperture Radar (GBSAR) is a tremendous example of the extended applications of Synthetic Aperture Radar (SAR). GBSAR is extremely useful in human-made structure observations, terrain mapping, landslide monitoring and many more. However, the process of designing and developing the GBSAR system is rather costly and time-consuming. It would be of a great advantage for system designers to have a realistic simulation and designing tool to anticipate the results before the implementation of the final design. In this paper, we are going to present the integrated simulation and designing tool that we have developed for a generic GBSAR system. We named it iSIM v2.0

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3

Crosetto, M., O. Monserrat, G. Luzi, N. Devanthéry, M. Cuevas-González, and A. Barra. "DATA PROCESSING AND ANALYSIS TOOLS BASED ON GROUND-BASED SYNTHETIC APERTURE RADAR IMAGERY." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W7 (September 13, 2017): 593–96. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w7-593-2017.

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The Ground-Based SAR (GBSAR) is a terrestrial remote sensing technique used to measure and monitor deformation. In this paper we describe two complementary approaches to derive deformation measurements using GBSAR data. The first approach is based on radar interferometry, while the second one exploits the GBSAR amplitude. In this paper we consider the so-called discontinuous GBSAR acquisition mode. The interferometric process is not always straightforward: it requires appropriate data processing and analysis tools. One of the main critical steps is phase unwrapping, which can critically affect the deformation measurements. In this paper we describe the procedure used at the CTTC to process and analyse discontinuous GBSAR data. In the second part of the paper we describe the approach based on GBSAR amplitude images and an image-matching method.

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Pieraccini, Massimiliano, Neda Rojhani, and Lapo Miccinesi. "Compressive Sensing for Ground Based Synthetic Aperture Radar." Remote Sensing 10, no. 12 (2018): 1960. http://dx.doi.org/10.3390/rs10121960.

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Compressive sensing (CS) is a recent technique that promises to dramatically speed up the radar acquisition. Previous works have already tested CS for ground-based synthetic aperture radar (GBSAR) performing preliminary simulations or carrying out measurements in controlled environments. The aim of this article is a systematic study on the effective applicability of CS for GBSAR with data acquired in real scenarios: an urban environment (a seven-storey building), an open-pit mine, and a natural slope (a glacier in the Italian Alps). The authors tested the most popular sets of orthogonal functions (the so-called ‘basis’) and three different recovery methods (l1-minimization, l2-minimization, orthogonal pursuit matching). They found that Haar wavelets as orthogonal basis is a reasonable choice in most scenarios. Furthermore, they found that, for any tested basis and recovery method, the quality of images is very poor with less than 30% of data. They also found that the peak signal–noise ratio (PSNR) of the recovered images increases linearly of 2.4 dB for each 10% increase of data.

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Hosseiny, B., J. Amini, and H. Aghababaei. "INTERFEROMETRIC PROCESSING OF A DEVELOPED MIMO GBSAR FOR DISPLACEMENT MONITORING." ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences X-4/W1-2022 (January 13, 2023): 301–6. http://dx.doi.org/10.5194/isprs-annals-x-4-w1-2022-301-2023.

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Abstract. This study demonstrates the interferometric processing experiments of our developed multiple-input multiple-output ground-based synthetic aperture radar (MIMO GBSAR) system. GBSAR systems are known as precise noncontact instruments for monitoring earth dynamics. In recent years W band MIMO radars have shown interesting potential in this field due to their low cost, compact size, and high phase sensitivity. MIMO capability enables the angular discrimination of multiple targets in the same range as the radar sensor. In our previous works, we developed a high-resolution MIMO GBSAR system based on the combination of MIMO radar and mechanical rail. Accordingly, this study investigates the developed system’s displacement monitoring capability by presenting a controlled experiment, using fixed and moving corner reflectors and gathering 36 time series of data. We compare and discuss the results obtained from MIMO GBSAR and MIMO radar configurations. The results show that our developed system highly agrees with MIMO radar’s interferometric measurements while providing a better target discrimination capability and higher signal noise ratio.

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Zhang, H. Y., Q. P. Zhai, L. Chen, et al. "THE MONITORING CASE OF GROUND-BASED SYNTHETIC APERTURE RADAR WITH FREQUENCY MODULATED CONTINUOUS WAVE SYSTEM." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W7 (September 13, 2017): 671–74. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w7-671-2017.

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The features of the landslide geological disaster are wide distribution, variety, high frequency, high intensity, destructive and so on. It has become a natural disaster with harmful and wide range of influence. The technology of ground-based synthetic aperture radar is a novel deformation monitoring technology developed in recent years. The features of the technology are large monitoring area, high accuracy, long distance without contact and so on. In this paper, fast ground-based synthetic aperture radar (Fast-GBSAR) based on frequency modulated continuous wave (FMCW) system is used to collect the data of Ma Liuzui landslide in Chongqing. The device can reduce the atmospheric errors caused by rapidly changing environment. The landslide deformation can be monitored in severe weather conditions (for example, fog) by Fast-GBSAR with acquisition speed up to 5 seconds per time. The data of Ma Liuzui landslide in Chongqing are analyzed in this paper. The result verifies that the device can monitor landslide deformation under severe weather conditions.

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7

Pieraccini, Massimiliano, and Lapo Miccinesi. "Cross-Pol Transponder with Frequency Shifter for Bistatic Ground-Based Synthetic Aperture Radar." Remote Sensing 10, no. 9 (2018): 1364. http://dx.doi.org/10.3390/rs10091364.

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Ground-based synthetic aperture radar (GBSAR) systems are popular remote sensing instruments for detecting the ground changes of landslides, glaciers, and open pits as well as for detecting small displacements of large structures, such as bridges and dams. Recently (2017), a novel mono/bistatic GBSAR configuration was proposed to acquire two different components of displacement of the targets in the field of view. This bistatic configuration relies on a transponder that consists—in its basic implementation—of just two antennas and an amplifier. The aim of this article was to design and experimentally test an improved transponder with cross-polarized antennas and frequency shifter that is able to prevent possible oscillations even at very high gain, as required in long-range applications. The transponder was successfully field-tested, and its measured gain was 91 dB gain.

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Wang, Zheng, Zhenhong Li, Yanxiong Liu, Junhuan Peng, Sichun Long, and Jon Mills. "A New Processing Chain for Real-Time Ground-Based SAR (RT-GBSAR) Deformation Monitoring." Remote Sensing 11, no. 20 (2019): 2437. http://dx.doi.org/10.3390/rs11202437.

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Due to the high temporal resolution (e.g., 10 s) required, and large data volumes (e.g., 360 images per hour) that result, there remain significant issues in processing continuous ground-based synthetic aperture radar (GBSAR) data. This includes the delay in creating displacement maps, the cost of computational memory, and the loss of temporal evolution in the simultaneous processing of all data together. In this paper, a new processing chain for real-time GBSAR (RT-GBSAR) is proposed on the basis of the interferometric SAR small baseline subset concept, whereby GBSAR images are processed unit by unit. The outstanding issues have been resolved by the proposed RT-GBSAR chain with three notable features: (i) low requirement of computational memory; (ii) insights into the temporal evolution of surface movements through temporarily-coherent pixels; and (iii) real-time capability of processing a theoretically infinite number of images. The feasibility of the proposed RT-GBSAR chain is demonstrated through its application to both a fast-changing sand dune and a coastal cliff with submillimeter precision.

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Wang, Yanping, Yang Song, Yun Lin, Yang Li, Yuan Zhang, and Wen Hong. "Interferometric DEM-Assisted High Precision Imaging Method for ArcSAR." Sensors 19, no. 13 (2019): 2921. http://dx.doi.org/10.3390/s19132921.

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Ground-based arc-scanning synthetic aperture radar (ArcSAR) is the novel ground-based synthetic aperture radar (GBSAR). It scans 360-degree surrounding scenes by the antenna attached to rotating boom. Therefore, compared with linear scanning GBSAR, ArcSAR has larger field of view. Although the feasibility of ArcSAR has been verified in recent years, its imaging algorithm still presents difficulties. The imaging accuracy of ArcSAR is affected by terrain fluctuation. For rotating scanning ArcSAR, even if targets in scenes have the same range and Doppler with antenna, if the heights of targets are different, their range migration will be different. Traditional ArcSAR imaging algorithms achieve imaging on reference plane. The height difference between reference plane and target in scenes will cause the decrease of imaging quality or even image defocusing because the range migration cannot be compensated correctly. For obtaining high-precision ArcSAR image, we propose interferometric DEM (digital elevation model)-assisted high precision imaging method for ArcSAR. The interferometric ArcSAR is utilized to acquire DEM. With the assist of DEM, target in scenes can be imaged on its actual height. In this paper, we analyze the error caused by ArcSAR imaging on reference plane. The method of extracting DEM on ground range for assisted ArcSAR imaging is also given. Besides, DEM accuracy and deformation monitoring accuracy of proposed method are analyzed. The effectiveness of the proposed method was verified by experiments.

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10

Long, Sichun, Aixia Tong, Ying Yuan, Zhenhong Li, Wenhao Wu, and Chuanguang Zhu. "New Approaches to Processing Ground-based SAR (GBSAR) Data for Deformation Monitoring." Remote Sensing 10, no. 12 (2018): 1936. http://dx.doi.org/10.3390/rs10121936.

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In this paper, aiming at the limitation of persistence scatterers (PS) points selection, a new method for selecting PS points has been introduced based on the average coherence coefficient, amplitude dispersion index, estimated signal-to-noise ratio and displacement standard deviation of multiple threshold optimization. The stability and quality of this method are better than that of a single model. In addition, an atmospheric correction model has also been proposed to estimate the atmospheric effects on Ground-based synthetic aperture radar (GBSAR) observations. After comparing the monitoring results before and after correction, we clearly found that the results are in good agreement with the actual observations after applying the proposed atmospheric correction approach.

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Academic literature on the topic 'Ground-Based Synthetic Aperture Radar (GBSAR)'

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