The GF-3 SAR Data Processor

Han, Bing; Ding, Chibiao; Zhong, Lihua; Liu, Jiayin; Qiu, Xiaolan; Hu, Yuxin; Lei, Bin

doi:10.3390/s18030835

Cited by 42 publications

(29 citation statements)

References 16 publications

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“…(2) Based on the result of step 1, the phase imbalances θ t and θ r are calculated by Equation (5); (3) Channel imbalances f T and f R are extracted by the internal calibration corresponding to imaging data; (4) According to the results of step 2 and 3, the distortion matrixes R and T are obtained; (5) The M is corrected to obtain the true scattering matrix (S) using Equation (9).…”

Section: Polarization Correction Methodsmentioning

confidence: 99%

“…So, GF-3 polarimetric calibration tasks face the challenge of guaranteeing the PolSAR data quality in each observing case. The product generation software of the GF-3 ground segment was developed by the Institute of Electronics, Chinese Academy of Sciences (IECAS) (details are described in [9]). In this study, we provide the methods used for the polarimetric error source analysis and calibration, and also the quality assessment results of GF-3 polarimetric data after polarimetric correction.…”

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confidence: 99%

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Error Source Analysis and Correction of GF-3 Polarimetric Data

et al. 2018

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The GaoFen-3 (GF-3) satellite is the first polarimetric synthetic aperture radar (PolSAR) satellite in China. With a designed in-orbit life of 8 years, it will provide large amounts of PolSAR data for ocean monitoring, disaster reduction, and many other applications. The polarimetric data quality is essential for all these applications, so the analysis and calibration of the polarimetric error sources are very important for GF-3. In this study, we established a full-link error model for GF-3 PolSAR system. Based on this model, we comprehensively analyzed the quantitative effects of the main error sources including the composition, figured out characteristics of the phase imbalance introduced by the antenna, and pointed out the error sources which have to be corrected. Furthermore, the polarimetric correction method for GF-3 PolSAR system is proposed. Finally, assisted by several external calibration experiments, polarimetric errors of GF-3 data are efficiently corrected during in-orbit-test phase. are 8 m/30 km while QPSII are 25 m/40 km. With these Full Polarized Modes, there are more than 40 beams in both right-and left-looking orientation, while the look angle ranges from 18.8 • to 42.8 • . Additionally, all beams have multiple options of bandwidth and pulse duration. With these multiple polarization modes, multiple beams and multiple bandwidths, GF-3 PolSAR can obtain more than 250 kinds of data under different system conditions, which may cause different polarimetric errors. So, GF-3 polarimetric calibration tasks face the challenge of guaranteeing the PolSAR data quality in each observing case. The product generation software of the GF-3 ground segment was developed by the Institute of Electronics, Chinese Academy of Sciences (IECAS) (details are described in [9]). In this study, we provide the methods used for the polarimetric error source analysis and calibration, and also the quality assessment results of GF-3 polarimetric data after polarimetric correction.

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Section: Polarization Correction Methodsmentioning

confidence: 99%

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confidence: 99%

Error Source Analysis and Correction of GF-3 Polarimetric Data

et al. 2018

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“…Gaofen-3 is Chinese first fully polarimetric C-band SAR satellite [12,13]. The satellite was launched in 2016.…”

Section: Gaofen-3 Sar Sensor and Datasetmentioning

confidence: 99%

Moving Target Detection with Modified Logarithm Background Subtraction and Its Application to the GF-3 Spotlight Mode

et al. 2019

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Spaceborne spotlight SAR mode has drawn attention due to its high-resolution capability, however, the studies about moving target detection with this mode are less. The paper proposes an image sequence-based method entitled modified logarithm background subtraction to detect ground moving targets with Gaofen-3 Single Look Complex (SLC) spotlight SAR images. The original logarithm background subtraction method is designed by our team for airborne SAR. It uses the subaperture image sequence to generate a background image, then detects moving targets by using image sequence to subtract background. When we apply the original algorithm to the spaceborne spotlight SAR data, a high false alarm problem occurs. To tackle the high false alarm problem due to the target’s low signal-to-noise-ratio (SNR) in spaceborne cases, several improvements are made. First, to preserve most of the moving target signatures, a low threshold CFAR (constant false alarm rate) detector is used to get the coarse detection. Second, because the moving target signatures have higher density than false detections in the coarse detection, a modified DBSCAN (density-based spatial-clustering-of-applications-with-noise) clustering method is then adopted to reduce false alarms. Third, the Kalman tracker is used to exclude the residual false detections, due to the real moving target signature having dynamic behavior. The proposed method is validated by real data, the shown results also prove the feasibility of the proposed method for both Gaofen-3 and other spaceborne systems.

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“…The Gaofen-3 (GF3) satellite, launched in 2016, was the first Chinese C-band polarimetric SAR, with high spatial resolution, multi-polarization imaging capability. And its remote sensing product can be applied in maritime surveillance, resource investigation, water environment monitoring, disaster prediction and so on [25][26][27][28][29]. GF3 is able to run in twelve different modes and one is the dual-polarization mode.…”

Section: Introductionmentioning

confidence: 99%

Validating GEV Model for Reflection Symmetry-Based Ocean Ship Detection with Gaofen-3 Dual-Polarimetric Data

et al. 2020

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The spaceborne synthetic aperture radar (SAR) is quite powerful in worldwide ocean observation, especially for ship monitoring, as a hot topic in ocean surveillance. The launched Gaofen-3 (GF3) satellite of China can provide C-band and multi-polarization SAR data, and one of its scientific applications is ocean ship detection. Compared with the single polarization system, polarimetric systems can be used for more effective ship detection. In this paper, a generalized extreme value (GEV)-based constant false alarm rate (CFAR) detector is proposed for ship detection in the ocean by using the reflection symmetry metric of dual-polarization. The reflection symmetry property shows big differences between the metallic targets at sea and the sea surface. In addition, the GEV statistical model is employed for reflection symmetry statistical distribution, which fits the reflection symmetry probability density function (pdf) well. Five dual-polarimetric GF3 stripmap ocean data sets are introduced in the paper, to show the contrast in enhancement by using reflection symmetry and to investigate the GEV model fit to the reflection symmetry metric. Additionally, with the detection experiments on the real GF3 datasets, the effectiveness and efficiency of the GEV model for reflection symmetry and the model-based ocean ship detector are verified.

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The GF-3 SAR Data Processor

Cited by 42 publications

References 16 publications

Error Source Analysis and Correction of GF-3 Polarimetric Data

Error Source Analysis and Correction of GF-3 Polarimetric Data

Moving Target Detection with Modified Logarithm Background Subtraction and Its Application to the GF-3 Spotlight Mode

Validating GEV Model for Reflection Symmetry-Based Ocean Ship Detection with Gaofen-3 Dual-Polarimetric Data

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