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Journal articles on the topic 'Ground based synthetic aperture radar'

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Author: Grafiati
Published: 10 March 2023

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1

Pieraccini, Massimiliano, Neda Rojhani, and Lapo Miccinesi. "Compressive Sensing for Ground Based Synthetic Aperture Radar." Remote Sensing 10, no. 12 (December 5, 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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2

Lee, Hoonyol, Younghun Ji, and Hyangsun Han. "Experiments on a Ground-Based Tomographic Synthetic Aperture Radar." Remote Sensing 8, no. 8 (August 18, 2016): 667. http://dx.doi.org/10.3390/rs8080667.

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3

Hosseiny, Benyamin, Jalal Amini, and Hossein Aghababaei. "Structural displacement monitoring using ground-based synthetic aperture radar." International Journal of Applied Earth Observation and Geoinformation 116 (February 2023): 103144. http://dx.doi.org/10.1016/j.jag.2022.103144.

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4

Hamdi, I., Y. Tounsi, M. Benjelloun, and A. Nassim. "Evaluation of the change in synthetic aperture radar imaging using transfer learning and residual network." Computer Optics 45, no. 4 (July 2021): 600–607. http://dx.doi.org/10.18287/2412-6179-co-814.

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Change detection from synthetic aperture radar images becomes a key technique to detect change area related to some phenomenon as flood and deformation of the earth surface. This paper proposes a transfer learning and Residual Network with 18 layers (ResNet-18) architecture-based method for change detection from two synthetic aperture radar images. Before the application of the proposed technique, batch denoising using convolutional neural network is applied to the two input synthetic aperture radar image for speckle noise reduction. To validate the performance of the proposed method, three known synthetic aperture radar datasets (Ottawa; Mexican and for Taiwan Shimen datasets) are exploited in this paper. The use of these datasets is important because the ground truth is known, and this can be considered as the use of numerical simulation. The detected change image obtained by the proposed method is compared using two image metrics. The first metric is image quality index that measures the similarity ratio between the obtained image and the image of the ground truth, the second metrics is edge preservation index, it measures the performance of the method to preserve edges. Finally, the method is applied to determine the changed area using two Sentinel 1 B synthetic aperture radar images of Eddahbi dam situated in Morocco.
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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 (December 17, 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 (December 17, 2019): 20–24. http://dx.doi.org/10.33093/jetap.2019.1.2.50.

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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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7

Hu, Jiyuan, Jiming Guo, Yi Xu, Lv Zhou, Shuai Zhang, and Kunfei Fan. "Differential Ground-Based Radar Interferometry for Slope and Civil Structures Monitoring: Two Case Studies of Landslide and Bridge." Remote Sensing 11, no. 24 (December 4, 2019): 2887. http://dx.doi.org/10.3390/rs11242887.

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Ground-based radar interferometry, which can be specifically classified as ground-based synthetic aperture radar (GB-SAR) and ground-based real aperture radar (GB-RAR), was applied to monitor the Liusha Peninsula landslide and Baishazhou Yangtze River Bridge. The GB-SAR technique enabled us to obtain the daily displacement evolution of the landslide, with a maximum cumulative displacement of 20 mm in the 13-day observation period. The virtual reality-based panoramic technology (VRP) was introduced to illustrate the displacement evolutions intuitively and facilitate the following web-based panoramic image browsing. We applied GB-RAR to extract the operational modes of the large bridge and compared them with the global positioning system (GPS) measurement. Through full-scale test and time-frequency result analysis from two totally different monitoring methods, this paper emphasized the 3-D display potentiality by combining the GB-SAR results with VRP, and focused on the detection of multi-order resonance frequencies, as well as the configure improvement of ground-based radars in bridge health monitoring.
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8

Jirousek, Matthias, Sebastian Iff, Simon Anger, and Markus Peichl. "GigaRad – a multi-purpose high-resolution ground-based radar – system concept, error correction strategies and performance verification." International Journal of Microwave and Wireless Technologies 7, no. 3-4 (April 16, 2015): 443–51. http://dx.doi.org/10.1017/s175907871500063x.

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Recently DLR has developed and constructed a new experimental radar instrument [5] for various applications such as radar signature collection, synthetic aperture radar/inverse synthetic aperture radarimaging, motion detection, tracking, etc., where high performance and high flexibility have been the key drivers for system design. Consequently the multi-purpose and multi-channel radar called GigaRad is operated in X and Ku band and allows an overall bandwidth of up to 6 GHz, resulting in a theoretical range resolution of up to 2.5 cm. Hence, primary obligation is a detailed analysis of various possible error sources, being of no or less relevance for low-resolution systems. A high degree of digital technology enables advanced signal processing and error correction to be applied. The paper outlines main technical features of the radar system, the basic error correction and absolute calibration strategy, frequency limitations, and illustrates some imaging results.
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9

Noferini, L., M. Pieraccini, D. Mecatti, G. Macaluso, G. Luzi, and C. Atzeni. "Long term landslide monitoring by ground‐based synthetic aperture radar interferometer." International Journal of Remote Sensing 27, no. 10 (May 2006): 1893–905. http://dx.doi.org/10.1080/01431160500353908.

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10

Anghel, Andrei, Zegang Ding, Holger Nies, Otmar Loffeld, David Atencia, Samuel G. Huaman, Aleksander Medella, et al. "Compact Ground-Based Interferometric Synthetic Aperture Radar: Short-Range Structural Monitoring." IEEE Signal Processing Magazine 36, no. 4 (July 2019): 42–52. http://dx.doi.org/10.1109/msp.2019.2894987.

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11

Broquetas, A., R. De Porrata, Ll Sagués, X. Fàbregas, and Ll Jofre. "Circular synthetic aperture radar (C-SAR) system for ground-based applications." Electronics Letters 33, no. 11 (1997): 988. http://dx.doi.org/10.1049/el:19970635.

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12

Palamà, R., M. Crosetto, O. Monserrat, A. Barra, B. Crippa, M. Mróz, N. Kotulak, M. Mleczko, and J. Rapinski. "ANALYSIS OF MINING-INDUCED TERRAIN DEFORMATION USING MULTITEMPORAL DISTRIBUTED SCATTERER SAR INTERFEROMETRY." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2022 (May 30, 2022): 321–26. http://dx.doi.org/10.5194/isprs-archives-xliii-b3-2022-321-2022.

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Abstract. This work addresses a methodology based on the Interferometric Synthetic Aperture Radar (InSAR) to analyse and monitor ground motion phenomena induced by underground mining activities, in the Legnica-Glogow Copper District, south-western Poland. Two stacks of ascending and descending Sentinel-1 Synthetic Aperture Radar (SAR) images are processed with a small baseline multitemporal approach. A simple method to select interferograms with high coherence and eliminated images with low redundancy is implemented to optimize the interferogram netwrork. The estimated displacement maps and time series show the effect of both linear and impulsive ground motion and are validated against Global Navigation Satellite System (GNSS) measurements.
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13

Song, Woo-Jin, Sung-Chul Woo, and Young-Kil Kwag. "Interference Impact Analysis of Ground Based Radar from Spaceborne High Resolution Synthetic Aperture Radar." Journal of Korean Institute of Electromagnetic Engineering and Science 19, no. 6 (June 30, 2008): 663–68. http://dx.doi.org/10.5515/kjkiees.2008.19.6.663.

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14

Yigit, Enes, Sevket Demirci, Caner Ozdemir, and Adnan Kavak. "A synthetic aperture radar-based focusing algorithm for B-scan ground penetrating radar imagery." Microwave and Optical Technology Letters 49, no. 10 (July 27, 2007): 2534–40. http://dx.doi.org/10.1002/mop.22724.

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15

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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16

Zhang, H. Y., Q. P. Zhai, L. Chen, Y. J. Liu, K. Q. Zhou, Y. S. Wang, and Y. D. Dou. "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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17

Brandewie, Aaron, and Robert Burkholder. "FEKO™ Simulation of Radar Scattering from Objects in Low Earth Orbit for ISAR Imaging." Applied Computational Electromagnetics Society 35, no. 11 (February 5, 2021): 1358–59. http://dx.doi.org/10.47037/2020.aces.j.351148.

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Objects in low earth orbit such as CubeSats and the International Space Station (ISS) move with constant velocity along a linear trajectory when viewed from a ground-based radar. The small change in attitude of the object as it flies overhead permits the generation of an inverse synthetic aperture radar (ISAR) image. In this paper, Altair’s FEKO™ software is used to model the monostatic radar scattering from the ISS as a function of frequency and aspect angle. The computed data is used for generating a simulated ISAR image from a ground-based radar. The system design requirements for the radar are calculated from the radar equation.
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18

Vincent, Shweta, Sharmila Francis, Kumudha Raimond, Tanweer Ali, and Prakash Kumar. "A novel planar antenna array for a ground-based synthetic aperture radar." Serbian Journal of Electrical Engineering 16, no. 2 (2019): 195–209. http://dx.doi.org/10.2298/sjee1902195v.

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19

Penner, Justin, and David Long. "Ground-Based 3D Radar Imaging of Trees Using a 2D Synthetic Aperture." Electronics 6, no. 1 (January 23, 2017): 11. http://dx.doi.org/10.3390/electronics6010011.

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20

Wang, Zheng, Zhenhong Li, and Jon P. Mills. "A New Nonlocal Method for Ground-Based Synthetic Aperture Radar Deformation Monitoring." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 11, no. 10 (October 2018): 3769–81. http://dx.doi.org/10.1109/jstars.2018.2864740.

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21

Pieraccini, M., and L. Miccinesi. "Cross‐pol long‐cable transponder for bistatic ground‐based synthetic aperture radar." Electronics Letters 54, no. 21 (October 2018): 1233–35. http://dx.doi.org/10.1049/el.2018.6081.

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22

Feng, Weike, Jean-Michel Friedt, Giovanni Nico, Suyun Wang, Gilles Martin, and Motoyuki Sato. "Passive Bistatic Ground-Based Synthetic Aperture Radar: Concept, System, and Experiment Results." Remote Sensing 11, no. 15 (July 25, 2019): 1753. http://dx.doi.org/10.3390/rs11151753.

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A passive bistatic ground-based synthetic aperture radar (PB-GB-SAR) system without a dedicated transmitter has been developed by using commercial-off-the-shelf (COTS) hardware for local-area high-resolution imaging and displacement measurement purposes. Different from the frequency-modulated or frequency-stepped continuous wave signal commonly used by GB-SAR, the continuous digital TV signal broadcast by a geostationary satellite has been adopted by PB-GB-SAR. In order to increase the coherence between the reference and surveillance channels, frequency and phase synchronization of multiple low noise blocks (LNBs) has been conducted. Then, the back-projection algorithm (BPA) and the range migration algorithm (RMA) have been modified for PB-GB-SAR to get the focused SAR image. Field experiments have been carried out to validate the designed PB-GB-SAR system and the proposed methods. It has been found that different targets within 100 m (like the fence, light pole, tree, and car) can be imaged by the PB-GB-SAR system. With a metallic plate moved on a positioner, it has been observed that the displacement of the target can be estimated by PB-GB-SAR with submillimeter accuracy.
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23

Wang, Peng, Cheng Xing, and Xiandong Pan. "Reservoir Dam Surface Deformation Monitoring by Differential GB-InSAR Based on Image Subsets." Sensors 20, no. 2 (January 10, 2020): 396. http://dx.doi.org/10.3390/s20020396.

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Ground-based synthetic aperture radar interferometry (GB-InSAR) enables the continuous monitoring of areal deformation and can thus provide near-real-time control of the overall deformation state of dam surfaces. In the continuous small-scale deformation monitoring of a reservoir dam structure by GB-InSAR, the ground-based synthetic aperture radar (GB-SAR) image acquisition may be interrupted by multiple interfering factors, such as severe changes in the meteorological conditions of the monitoring area and radar equipment failures. As a result, the observed phases before and after the interruption cannot be directly connected, and the original spatiotemporal datum for the deformation measurement is lost, making the follow-up monitoring results unreliable. In this study, a multi-threshold strategy was first adopted to select coherent point targets (CPTs) by using successive GB-SAR image sequences. Then, we developed differential GB-InSAR with image subsets based on the CPTs to solve the dam surface deformation before and after aberrant interruptions. Finally, a deformation monitoring experiment was performed on an actual large reservoir dam. The effectiveness and accuracy of the abovementioned method were verified by comparing the results with measurements by a reversed pendulum monitoring system.
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24

Lee, Hoonyol, and Jihyun Moon. "Analysis of a Bistatic Ground-Based Synthetic Aperture Radar System and Indoor Experiments." Remote Sensing 13, no. 1 (December 26, 2020): 63. http://dx.doi.org/10.3390/rs13010063.

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Recent advancement of satellite synthetic aperture radar (SAR) techniques require more sophisticated system configurations such as the use of bistatic antennas or multi-frequencies. A ground-based experiment is a cost-effective and efficient way to evaluate those new configurations especially in the early stage of the system development. In this paper, a ground-based synthetic aperture radar (GB-SAR) system was constructed and operated in a bistatic mode at Ku-band where a receiving antenna (Rx) follows a transmitting antenna (Tx) separated by a baseline B. A new bistatic GB-SAR focusing algorithm was developed by modifying a conventional range-Doppler algorithm (RDA), and its performance has been evaluated by comparing the results with those from a back-projection algorithm (BPA). The results showed good performance of RDA at far range approaching nominal resolutions of 9.4 cm in range and 4.5 cm in azimuth, but limited quality at near range due to the approximation used in RDA. Signals from three trihedral corner reflectors (CR) reduced with increasing B, showing a typical bidirectional scattering behavior of CR. This GB-SAR system will be a testbed for new SAR imaging configurations with variations in antenna positions and target properties.
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Nekoee, M., and J. Amini. "USING A PULSE INTEGRATION TECHNIQUE FOR IMPROVEMENT OF RECEIVED SIGNAL POWER IN GROUND BASED SAR SYSTEM." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W18 (October 18, 2019): 815–19. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w18-815-2019.

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Abstract. Today, radar imaging with synthetic aperture has obtained an important place in radar remote sensing, in such a way that it is utilized in the variety of space borne, airborne and ground platforms to extract information from different desired surfaces. Among these, Ground Based Synthetic Aperture Radars (GB-SAR) has numerous applications such as space system calibration, change detection, target detection, surface displacement determination and condition monitoring. In general, in GB-SAR systems, given that the power of the transmitted signal is low, the received signal is also of low power, and subsequently the presence of target in the image is of lower probability. Therefore, in this research, a method is proposed to increase the received signal power based on pulse integration by a non-Coherent method which results in an increase in the Signal to Noise Ratio (SNR), thereby increasing the focusing power on the target. In this way, a large number of samples can be received in the data collection section and the gain can be therefore increased by integrating the number of received pulses. According to the −3.22 dB Improvement of focusing evaluation criterion (PSLR), it is shown in this research that the accuracy of the target detection is increased. Finally, the effect of the number of pulses integrated on the noise presence and accuracy of the target detection is described.
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26

Bähnemann, Rik, Nicholas Lawrance, Lucas Streichenberg, Jen Jen Chung, Michael Pantic, Alexander Grathwohl, Christian Waldschmidt, and Roland Siegwart. "Under the Sand: Navigation and Localization of a Micro Aerial Vehicle for Landmine Detection with Ground-Penetrating Synthetic Aperture Radar." Field Robotics 2, no. 1 (March 10, 2022): 1028–67. http://dx.doi.org/10.55417/fr.2022034.

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Ground-penetrating radar mounted on a micro aerial vehicle (MAV) is a promising tool to assist humanitarian landmine clearance. However, the quality of synthetic aperture radar images depends on accurate and precise motion estimation of the radar antennas as well as generating informative viewpoints with the MAV. This paper presents a complete and automatic airborne ground-penetrating synthetic aperture radar (GPSAR) system. The system consists of a spatially calibrated and temporally synchronized industrial grade sensor suite that enables navigation above ground level, radar imaging, and optical imaging. A custom mission planning framework allows generation and automatic execution of stripmap and circular GPSAR trajectories controlled above ground level as well as aerial imaging survey flights. A factor graph based state estimator fuses measurements from dual receiver real-time kinematic (RTK) global navigation satellite system (GNSS) and an inertial measurement unit (IMU) to obtain precise, high-rate platform positions and orientations. Ground truth experiments showed sensor timing as accurate as 0.8 µs and as precise as 0.1 µs with localization rates of 1 kHz. The dual position factor formulation improves online localization accuracy up to 40 % and batch localization accuracy up to 59 % compared to a single position factor with uncertain heading initialization. Our field trials validated a localization accuracy and precision that enables coherent radar measurement addition and detection of radar targets buried in sand. This validates the potential as an aerial landmine detection system.
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27

Thakur, P. K., R. D. Garg, S. P. Aggarwal, P. K. Garg, and J. Shi. "Snow density retrieval using SAR data: algorithm validation and applications in part of North Western Himalaya." Cryosphere Discussions 7, no. 3 (May 3, 2013): 1927–60. http://dx.doi.org/10.5194/tcd-7-1927-2013.

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Abstract. The current study has been done using Polarimetric Synthetic Aperture Radar (SAR) data to estimate the dry snow density in Manali sub-basin of Beas River located in state of Himachal Pradesh, India. SAR data from Radarsat-2 (RS2), Environmental Satellite (ENVISAT), Advanced Synthetic Aperture Radar (ASAR) and Advanced Land Observing Satellite (ALOS)-Phased Array type L-band Synthetic Aperture Radar (PALSAR) have been used. The SAR based inversion models were implemented separately for fully polarimetric RS2, PALSAR and dual polarimetric ASAR Alternate polarization System (APS) datasets in Mathematica and MATLAB software and have been used for finding out dry snow dielectric constant and snow density. Masks for forest, built area, layover and shadow were considered in estimating snow parameters. Overall accuracy in terms of R2 value and Root Mean Square Error (RMSE) was calculated as 0.85 and 0.03 g cm−3 for snow density based on the ground truth data. The retrieved snow density is highly useful for snow avalanche and snowmelt runoff modeling related studies of this region.
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28

Lin, Yun, Yutong Liu, Yanping Wang, Shengbo Ye, Yuan Zhang, Yang Li, Wei Li, Hongquan Qu, and Wen Hong. "Frequency Domain Panoramic Imaging Algorithm for Ground-Based ArcSAR." Sensors 20, no. 24 (December 8, 2020): 7027. http://dx.doi.org/10.3390/s20247027.

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The ground-based arc-scanning synthetic aperture radar (ArcSAR) is capable of 360° scanning of the surroundings with the antenna fixed on a rotating arm. ArcSAR has much wider field of view when compared with conventional ground-based synthetic aperture radar (GBSAR) scanning on a linear rail. It has already been used in deformation monitoring applications. This paper mainly focuses on the accurate and fast imaging algorithms for ArcSAR. The curvature track makes the image focusing challenging and, in the classical frequency domain, fast imaging algorithms that are designed for linear rail SAR cannot be readily applied. This paper proposed an efficient frequency domain imaging algorithm for ArcSAR. The proposed algorithm takes advantage of the angular shift-invariant property of the ArcSAR signal, and it deduces the accurate matched filter in the angular-frequency domain, so panoramic images in polar coordinates with wide swath can be obtained at one time without segmenting strategy. When compared with existing ArcSAR frequency domain algorithms, the proposed algorithm is more accurate and efficient, because it has neither far range nor narrow beam antenna restrictions. The proposed method is validated by both simulation and real data. The results show that our algorithm brings the quality of image close to the time domain back-projection (BP) algorithm at a processing efficiency about two orders of magnitude better, and it has better image quality than the existing frequency domain Lee’s algorithm at a comparable processing speed.
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29

Monteith, Albert R., Lars M. H. Ulander, and Stefano Tebaldini. "Calibration of a Ground-Based Array Radar for Tomographic Imaging of Natural Media." Remote Sensing 11, no. 24 (December 6, 2019): 2924. http://dx.doi.org/10.3390/rs11242924.

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Ground-based tomographic radar measurements provide valuable knowledge about the electromagnetic scattering mechanisms and temporal variations of an observed scene and are essential in preparation for space-borne tomographic synthetic aperture radar (SAR) missions. Due to the short range between the radar antennas and a scene being observed, the tomographic radar observations are affected by several systematic errors. This article deals with the modelling and calibration of three systematic errors: mutual antenna coupling, magnitude and phase errors and the pixel-variant impulse response of the tomographic image. These errors must be compensated for so that the tomographic images represent an undistorted rendering of the scene reflectivity. New calibration methods were described, modelled and validated using experimental data. The proposed methods will be useful for future ground-based tomographic radar experiments in preparation for space-borne SAR missions.
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30

Maślikowski, Łukasz, and Jacek Misiurewicz. "Nonuniform Spatial Sampling in a Ground-Based Noise SAR." International Journal of Electronics and Telecommunications 57, no. 1 (March 1, 2011): 71–75. http://dx.doi.org/10.2478/v10177-011-0010-2.

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Nonuniform Spatial Sampling in a Ground-Based Noise SARThe paper presents an idea of nonuniform spatial sampling applied to a noise synthetic aperture radar. In certain cases it is desirable to limit the number of spatial (along-track) domain samples acquired in a SAR radar because of external constraints on sampling frequency or on the overall number of samples - e.g. in order to economy on time or power consumed. Lowering number of samples taken may, however, lead to spatial aliasing and incorrect reconstruction of the image. Nonuniform sampling allows to reduce the aliasing effect and reconstruct the image better. This technique can be applied with standard reconstruction methods, but it works best together with Compressive Sensing reconstruction algorithms. The idea will be verified with an experimental noise SAR built at ISE PW.
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31

Weinman, J. A., F. S. Marzano, W. J. Plant, A. Mugnai, and N. Pierdicca. "Rainfall observation from X-band, space-borne, synthetic aperture radar." Natural Hazards and Earth System Sciences 9, no. 1 (February 4, 2009): 77–84. http://dx.doi.org/10.5194/nhess-9-77-2009.

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Abstract. Satellites carrying X-band Synthetic Aperture Radars (SAR) have recently been launched by several countries. These provide new opportunities to measure precipitation with higher spatial resolution than has heretofore been possible. Two algorithms to retrieve precipitation from such measurements over land have been developed, and the retrieved rainfall distributions were found to be consistent. A maritime rainfall distribution obtained from dual frequency (X and C-band) data was used to compute the Differential Polarized Phase Shift. The computed Differential Polarized Phase Shift compared well with the value measured from space. Finally, we show a comparison between a recent X-band SAR image of a precipitation distribution and an observation of the same rainfall from ground-based operational weather radar. Although no quantitative comparison of retrieved and conventional rainfall distributions could be made with the available data at this time, the results presented here point the way to such comparisons.
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Chojka, Agnieszka, Piotr Artiemjew, and Jacek Rapiński. "RFI Artefacts Detection in Sentinel-1 Level-1 SLC Data Based On Image Processing Techniques." Sensors 20, no. 10 (May 21, 2020): 2919. http://dx.doi.org/10.3390/s20102919.

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Interferometric Synthetic Aperture Radar (InSAR) data are often contaminated by Radio-Frequency Interference (RFI) artefacts that make processing them more challenging. Therefore, easy to implement techniques for artefacts recognition have the potential to support the automatic Permanent Scatterers InSAR (PSInSAR) processing workflow during which faulty input data can lead to misinterpretation of the final outcomes. To address this issue, an efficient methodology was developed to mark images with RFI artefacts and as a consequence remove them from the stack of Synthetic Aperture Radar (SAR) images required in the PSInSAR processing workflow to calculate the ground displacements. Techniques presented in this paper for the purpose of RFI detection are based on image processing methods with the use of feature extraction involving pixel convolution, thresholding and nearest neighbor structure filtering. As the reference classifier, a convolutional neural network was used.
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Michelini, Alberto, Francesco Coppi, Alberto Bicci, and Giovanni Alli. "SPARX, a MIMO Array for Ground-Based Radar Interferometry." Sensors 19, no. 2 (January 10, 2019): 252. http://dx.doi.org/10.3390/s19020252.

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Ground-Based SAR Interferometry (GB-InSAR) is nowadays a proven technique widely used for slope monitoring in open pit mines and landslide control. Traditional GB-InSAR techniques involve transmitting and receiving antennas moving on a scanner to achieve the desired synthetic aperture. Mechanical movement limits the acquisition speed of the SAR image. There is a need for faster acquisition time as it plays an important role in correcting rapidly varying atmospheric effects. Also, a fast imaging radar can extend the applications to the measurement of vibrations of large structures. Furthermore, the mechanical assembly put constraints on the transportability and weight of the system. To overcome these limitations an electronically switched array would be preferable, which however faces enormous technological and cost difficulties associated to the large number of array elements needed. Imaging Multiple-Input Multiple Output (MIMO) radars can be used as a significant alternative to usual mechanical SAR and full array systems. This paper describes the ground-based X-band MIMO radar SPARX recently developed by IDS GeoRadar in order to overcome the limits of IDS GeoRadar’s well-established ground based interferometric SAR systems. The SPARX array consists of 16 transmit and 16 receive antennas, organized in independent sub-modules and geometrically arranged in order to synthesize an equally spaced virtual array of 256 elements.
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Panzner, Berthold, Andreas Jöstingmeier, and Abbas Omar. "Radar Signatures of Complex Buried Objects in Ground Penetrating Radar." International Journal of Electronics and Telecommunications 57, no. 1 (March 1, 2011): 9–14. http://dx.doi.org/10.2478/v10177-011-0001-3.

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Radar Signatures of Complex Buried Objects in Ground Penetrating RadarThe evaluation of radar signatures of buried objects for three experimental ground penetrating radar setups will be addressed in this paper. The contribution will present corresponding results and experiences. The performance of the imaging capabilities of the designed radar system will be assessed by reconstruction of complex shaped test objects, which have been placed within the ground. The influence of system parameters of the ground penetrating radar have been varied systematically in order to analyze their effects on the image quality. Among the modified parameters are the step size in transverse plane, height of the antenna over ground, frequency range, frequency points, antennas and varying instrument settings. A signal processing technique based on synthetic aperture radar has been applied on the measured raw data. The focus radius around a specific target has been analyzed concerning the compromise between image quality and processing time. The experiments demonstrate that the designed ground penetrating radar systems are capable for detection of buried objects with high resolution.
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Pieraccini, Massimiliano, and Lapo Miccinesi. "Cross-Pol Transponder with Frequency Shifter for Bistatic Ground-Based Synthetic Aperture Radar." Remote Sensing 10, no. 9 (August 28, 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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36

Kudryashov, V. V., K. A. Lukin, V. P. Palamarchuk, and P. L. Vyplavin. "COHERENT RADIOMETRIC IMAGING WITH A Ka-BAND GROUND-BASED SYNTHETIC APERTURE NOISE RADAR." Telecommunications and Radio Engineering 72, no. 8 (2013): 699–710. http://dx.doi.org/10.1615/telecomradeng.v72.i8.50.

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Weiwei, Wang, Liao Guisheng, Zhu ShengQi, and Zhang Jie. "Compressive sensing‐based ground moving target indication for dual‐channel synthetic aperture radar." IET Radar, Sonar & Navigation 7, no. 8 (October 2013): 858–66. http://dx.doi.org/10.1049/iet-rsn.2012.0135.

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Oveis, Amir Hosein, and Mohammad Ali Sebt. "Compressed sensing‐based ground MTI with clutter rejection scheme for synthetic aperture radar." IET Signal Processing 11, no. 2 (April 2017): 155–64. http://dx.doi.org/10.1049/iet-spr.2016.0156.

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Chen, Wei, Qihui Zheng, Haibing Xiang, Xu Chen, and Tetsuro Sakai. "Forest Canopy Height Estimation Using Polarimetric Interferometric Synthetic Aperture Radar (PolInSAR) Technology Based on Full-Polarized ALOS/PALSAR Data." Remote Sensing 13, no. 2 (January 6, 2021): 174. http://dx.doi.org/10.3390/rs13020174.

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Forest canopy height is a basic metric characterizing forest growth and carbon sink capacity. Based on full-polarized Advanced Land Observing Satellite/Phased Array type L-band Synthetic Aperture Radar (ALOS/PALSAR) data, this study used Polarimetric Interferometric Synthetic Aperture Radar (PolInSAR) technology to estimate forest canopy height. In total the four methods of differential DEM (digital elevation model) algorithm, coherent amplitude algorithm, coherent phase-amplitude algorithm and three-stage random volume over ground algorithm (RVoG_3) were proposed to obtain canopy height and their accuracy was compared in consideration of the impacts of coherence coefficient and range slope levels. The influence of the statistical window size on the coherence coefficient was analyzed to improve the estimation accuracy. On the basis of traditional algorithms, time decoherence was performed on ALOS/PALSAR data by introducing the change rate of Landsat NDVI (Normalized Difference Vegetation Index). The slope in range direction was calculated based on SRTM (Shuttle Radar Topography Mission) DEM data and then introduced into the s-RVoG (sloped-Random Volume over Ground) model to optimize the canopy height estimation model and improve the accuracy. The results indicated that the differential DEM algorithm underestimated the canopy height significantly, while the coherent amplitude algorithm overestimated the canopy height. After removing the systematic coherence, the overestimation of the RVoG_3 model was restrained, and the absolute error decreased from 23.68 m to 4.86 m. With further time decoherence, the determination coefficient increased to 0.2439. With the introduction of range slope, the s-RVoG model shows improvement compared to the RVoG model. Our results will provide a reference for the appropriate algorithm selection and optimization for forest canopy height estimation using full-polarized L-band synthetic aperture radar (SAR) data for forest ecosystem monitoring and management.
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40

Dubyna, O. F., O. V. Andreiev, T. M. Nikitchuk, I. V. Puleko, S. S. Hatsenko, and V. V. Kliaznyka. "SYNTHESIZING THE ANTENNA APERTURE USING SIGNALS FROM GROUND-BASED RADAR STATIONS FROM A SPACE CARRIER." Проблеми створення, випробування, застосування та експлуатації складних інформаційних систем, no. 22 (August 4, 2022): 69–78. http://dx.doi.org/10.46972/2076-1546.2022.22.06.

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Today, one of the priority directions of the aerospace industry of Ukraine is the creation of effective aerospace intelligence. Remote sensing of the Earth in the optical range provides the opportunity to obtain images of the Earth's surface for use in the military sphere and the national economy. For this, various sensors are used, which, as a rule, register radiation reflected from the surface of the Earth and objects located on it. Surveying the Earth's surface from space vehicles in the radio range allows solving a wide range of tasks. At the same time, the antenna irradiates the earth's surface with a radio signal with known parameters and receives the signal reflected from the surface over a relatively large area of the carrier's trajectory. When using a side view of the earth's surface to increase the angular separation by the path range, the artificial synthesis of the antenna aperture has become widely used. Artificially synthesizing the antenna aperture is carried out at the stage of coherent or incoherent processing of the reflected signal on a certain section of the carrier's trajectory. At the same time, the parameters of the reference trajectory signal are considered to be known with accuracy to the random phase. In contrast to the classical active methods of antenna aperture synthesis, which require the availability of information about the parameters of the radiated signal, with the passive method of antenna aperture synthesis, the parameters of the received signal are determined by the type of radio radiation source and are a priori unknown. When passively synthesizing the antenna aperture based on ground radar signals, both the maximum possible size of the synthesized aperture and the conditions for determining the azimuthal direction to the source of radio radiation depend on the parameters of the signal emitted by the radar. The paper analyzes the orbit parameters of the spacecraft, which ensure the fulfillment of the condition of the unambiguity of the determination of the azimuthal direction to the source of radio radiation and determine the resolution in terms of the path range during the passive synthesis of the antenna aperture based on the signals of typical radars operating in the pulse mode. Keywords: spacecraft; source of radio emission; resolution; antenna synthesized aperture.
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41

Palamà, Riccardo, Michele Crosetto, Jacek Rapinski, Anna Barra, María Cuevas-González, Oriol Monserrat, Bruno Crippa, Natalia Kotulak, Marek Mróz, and Magdalena Mleczko. "A Multi-Temporal Small Baseline Interferometry Procedure Applied to Mining-Induced Deformation Monitoring." Remote Sensing 14, no. 9 (May 2, 2022): 2182. http://dx.doi.org/10.3390/rs14092182.

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This work addresses a methodology based on the interferometric synthetic aperture radar (InSAR) applied to analyze and monitor ground-motion phenomena induced by underground mining activities in the Legnica-Glogow copper district, south-western Poland. The adopted technique employs an InSAR processing chain that exploits a stack of Sentinel-1 synthetic aperture radar (SAR) images using a small baseline multitemporal approach. Interferograms with small temporal baselines are first selected, then their network is optimized and reduced to eliminate noisy data, in order to mitigate the effect of decorrelation sources related to seasonal phenomena, i.e., snow and vegetation growth, and to the radar acquisition geometry. The atmospheric disturbance is mitigated using a spatio-temporal filter based on the nonequispaced fast Fourier transform. The estimated displacement maps and time series show the effect of both linear and impulsive ground motion and are validated against global navigation satellite system (GNSS) measurements. In this context, a significant threat to the built environment is represented by seismic tremors triggered by underground mining activities, which are analyzed using the proposed method to integrate the information gathered by in situ seismometer devices.
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42

Rao, Anirudh, Jungkyo Jung, Vitor Silva, Giuseppe Molinario, and Sang-Ho Yun. "Earthquake building damage detection based on synthetic-aperture-radar imagery and machine learning." Natural Hazards and Earth System Sciences 23, no. 2 (February 23, 2023): 789–807. http://dx.doi.org/10.5194/nhess-23-789-2023.

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Abstract. This article presents a framework for semi-automated building damage assessment due to earthquakes from remote-sensing data and other supplementary datasets, while also leveraging recent advances in machine-learning algorithms. The framework integrates high-resolution building inventory data with earthquake ground shaking intensity maps and surface-level changes detected by comparing pre- and post-event InSAR (interferometric synthetic aperture radar) images. We demonstrate the use of ensemble models in a machine-learning approach to classify the damage state of buildings in the area affected by an earthquake. Both multi-class and binary damage classification are attempted for four recent earthquakes, and we compare the predicted damage labels with ground truth damage grade labels reported in field surveys. For three out of the four earthquakes studied, the model is able to identify over 50 % or nearly half of the damaged buildings successfully when using binary classification. Multi-class damage grade classification using InSAR data has rarely been attempted previously, and the case studies presented in this report represent one of the first such attempts using InSAR data.
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Miccinesi, Lapo, Tommaso Consumi, Alessandra Beni, and Massimiliano Pieraccini. "W-band MIMO GB-SAR for Bridge Testing/Monitoring." Electronics 10, no. 18 (September 14, 2021): 2261. http://dx.doi.org/10.3390/electronics10182261.

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Interferometric radars are widely used for static and dynamic monitoring of large structures such as bridges, culverts, wind turbine towers, chimneys, masonry towers, stay cables, buildings, and monuments. Most of these radars operate in Ku-band (17 GHz). Nevertheless, a higher operative frequency could allow the design of smaller, lighter, and faster equipment. In this paper, a fast MIMO-GBSAR (Multiple-Input Multiple-Output Ground-Based Synthetic Aperture Radar) operating in W-band (77 GHz) has been proposed. The radar can complete a scan in less than 8 s. Furthermore, as its overall dimension is smaller than 230 mm, it can be easily fixed to the head of a camera tripod, which makes its deployment in the field very easy, even by a single operator. The performance of this radar was tested in a controlled environment and in a realistic case study.
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Guo, Yanhui, Zhiquan Yang, Yi Yang, Zhijun Kong, Caikun Gao, and Weiming Tian. "Experimental Study on Deformation Monitoring of Large Landslide in Reservoir Area of Hydropower Station Based on GB-InSAR." Advances in Civil Engineering 2021 (July 8, 2021): 1–11. http://dx.doi.org/10.1155/2021/5586340.

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The monitoring and early warning of a landslide in the reservoir area of a hydropower station are of great significance in the dam structure of the hydropower station and in the safety of people’s life and property on the reservoir bank. In this study, a new ground-based interferometric synthetic aperture radar system LKR-05-KU-S100 was used to carry out field monitoring tests on Lagu landslide and Xiaozhaju landslide of Dahuaqiao hydropower station and No. 1 landslide on the left bank of Xiaowan hydropower station on the Lancang river. The results show that, during the monitoring period, Lagu landslide of Dahuaqiao hydropower station and No. 1 landslide on the left bank of Xiaowan hydropower station are basically stable, and the deformation trend of Xiaozhaju landslide is obvious so it should undergo continuous monitoring. At the same time, the field monitoring test also shows that the new ground-based interferometric synthetic aperture radar system LKR-05-KU-S100 has the advantages of high precision and long-distance, all-day, all-weather, and large-scale monitoring and has unique advantages and broad application prospects for the overall deformation monitoring of large landslides in the reservoir area.
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45

He, Zhen-Yu, Yang Yang, Wu Chen, and Duo-Jie Weng. "Moving Target Imaging Using GNSS-Based Passive Bistatic Synthetic Aperture Radar." Remote Sensing 12, no. 20 (October 14, 2020): 3356. http://dx.doi.org/10.3390/rs12203356.

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Current studies of global navigation satellite systems (GNSS)-based bistatic synthetic aperture radar (GNSS-SAR) is focused on static objects on land. However, moving target imaging is also very significant for modern SAR systems. Imaging a moving target has two main problems. One is the unknown range cell migration; the other is the motion parameter estimation, such as the target’s velocity. This paper proposes a moving target imaging formation algorithm for GNSS-SAR. First, an approximate bistatic range history is derived to describe the phase variation of the target signal along the azimuth time. Then, a keystone transform is employed to correct the range cell migration. To address the motion parameter estimation, a chirp rate estimation method based on short-time Fourier transform and random sample consensus is proposed with high processing efficiency and robust estimation errors in low signal-to-noise ratio scenes. The estimated chirp rate can calculate the target’s velocity. Finally, azimuth compression derivation is performed to accomplish GNSS-SAR imaging. A maritime experimental campaign is conducted to validate the effectiveness of the proposed algorithm. The two cargo ships in the SAR images have good accordance with the ground truth in terms of the target-to-receiver vertical distances along the range and the ships’ length along the cross-range.
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46

Wang, Wen-Qin. "Detecting and Mitigating Wind Turbine Clutter for Airspace Radar Systems." Scientific World Journal 2013 (2013): 1–8. http://dx.doi.org/10.1155/2013/385182.

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It is well recognized that a wind turbine has a large radar cross-section (RCS) and, due to the movement of the blades, the wind turbine will generate a Doppler frequency shift. This scattering behavior may cause severe interferences on existing radar systems including static ground-based radars and spaceborne or airborne radars. To resolve this problem, efficient techniques or algorithms should be developed to mitigate the effects of wind farms on radars. Herein, one transponder-based mitigation technique is presented. The transponder is not a new concept, which has been proposed for calibrating high-resolution imaging radars. It modulates the radar signal in a manner that the retransmitted signals can be separated from the scene echoes. As wind farms often occupy only a small area, mitigation processing in the whole radar operation will be redundant and cost inefficient. Hence, this paper uses a transponder to determine whether the radar is impacted by the wind farms. If so, the effects of wind farms are then mitigated with subsequent Kalman filtering or plot target extraction algorithms. Taking airborne synthetic aperture radar (SAR) and pulse Doppler radar as the examples, this paper provides the corresponding system configuration and processing algorithms. The effectiveness of the mitigation technique is validated by numerical simulation results.
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Oveis, Amir Hosein, and Mohammad Ali Sebt. "Dictionary-Based Principal Component Analysis for Ground Moving Target Indication by Synthetic Aperture Radar." IEEE Geoscience and Remote Sensing Letters 14, no. 9 (September 2017): 1594–98. http://dx.doi.org/10.1109/lgrs.2017.2724854.

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48

Roy, Ashish K., S. A. Gangal, and C. Bhattacharya. "Calibration of High-Resolution Synthetic Aperture Radar (SAR) Image Features by Ground-Based Experiments." IETE Journal of Research 63, no. 3 (January 19, 2017): 381–91. http://dx.doi.org/10.1080/03772063.2016.1272435.

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49

Atzeni, C., M. Barla, M. Pieraccini, and F. Antolini. "Early Warning Monitoring of Natural and Engineered Slopes with Ground-Based Synthetic-Aperture Radar." Rock Mechanics and Rock Engineering 48, no. 1 (February 21, 2014): 235–46. http://dx.doi.org/10.1007/s00603-014-0554-4.

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50

Xu, Bing, Zhiwei Li, Yan Zhu, Jiancun Shi, and Guangcai Feng. "SAR Interferometric Baseline Refinement Based on Flat-Earth Phase without a Ground Control Point." Remote Sensing 12, no. 2 (January 9, 2020): 233. http://dx.doi.org/10.3390/rs12020233.

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Interferometric baseline estimation is a key procedure of interferometric synthetic aperture radar (SAR) data processing. The error of the interferometric baseline affects not only the removal of the flat-earth phase, but also the transformation coefficient between the topographic phase and elevation, which will affect the topographic phase removal for differential interferometric SAR (D-InSAR) and the accuracy of the final generated digital elevation model (DEM) product for interferometric synthetic aperture (InSAR). To obtain a highly accurate interferometric baseline, this paper firstly investigates the geometry of InSAR imaging and establishes a rigorous relationship between the interferometric baseline and the flat-earth phase. Then, a baseline refinement method without a ground control point (GCP) is proposed, where a relevant theoretical model and resolving method are developed. Synthetic and real SAR datasets are used in the experiments, and a comparison with the conventional least-square (LS) baseline refinement method is made. The results demonstrate that the proposed method exhibits an obvious improvement over the conventional LS method, with percentages of up to 51.5% in the cross-track direction. Therefore, the proposed method is effective and advantageous.
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