Multichannel False-target Discrimination in SAR Images Based on Sub-aperture and Full-aperture Feature Learning

MA Lin; PAN Zongxu; HUANG Zhongling; HAN Bing; HU Yuxin; ZHOU Xiao; LEI Bin

doi:10.12000/JR20106

Volume 10 Issue 1

Feb. 2021

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Article Navigation > Journal of Radars > 2021 > 10(1): 159-172

Zhang Yue, Zou Huanxin, Shao Ningyuan, et al.. Fast superpixel segmentation algorithm for PolSAR images[J]. Journal of Radars, 2017, 6(5): 564–573. DOI: 10.12000/JR17018

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MA Lin, PAN Zongxu, HUANG Zhongling, et al. Multichannel false-target discrimination in SAR images based on sub-aperture and full-aperture feature learning[J]. Journal of Radars, 2021, 10(1): 159–172. doi: 10.12000/JR20106

Zhang Yue, Zou Huanxin, Shao Ningyuan, et al.. Fast superpixel segmentation algorithm for PolSAR images[J]. Journal of Radars, 2017, 6(5): 564–573. DOI: 10.12000/JR17018

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Multichannel False-target Discrimination in SAR Images Based on Sub-aperture and Full-aperture Feature Learning

DOI: 10.12000/JR20106 CSTR: 32380.14.JR20106

MA Lin^{1, 2, 3},
PAN Zongxu^{1, 2, 3
,
,},
HUANG Zhongling^{1, 2, 3},
HAN Bing^{1, 2, 3},
HU Yuxin^{1, 2, 3},
ZHOU Xiao^{1, 2},
LEI Bin^{1, 2, 3}

1.
Aerospace Information Research Institute, Chinese Academy of Science, Beijing 100190, China
2.
Key Laboratory of Technology in Geo-spatial Information Processing and Application System, Beijing 100190, China
3.
University of Chinese Academy of Sciences, Beijing 100049, China

Funds: The National Natural Science Foundation of China (61701478)

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Corresponding author: PAN Zongxu, zxpan@mail.ie.ac.cn
Received Date: 2020-07-23
Rev Recd Date: 2020-09-09

Available Online: 2020-10-09

Publish Date: 2021-02-25

Abstract

Abstract

False targets caused by multichannel Synthetic Aperture Radar (SAR) are similar to a defocused ship in both shape and texture, making it difficult to discriminate in the full-aperture SAR image. To address the issue of false alarms caused by such false targets, this paper proposes a multichannel SAR false-target discrimination method based on sub-aperture and full-aperture feature learning. First, amplitude calculation is performed on complex SAR images to obtain the amplitude images, and transfer learning is utilized to extract the full-aperture features from the amplitude images. Then, sub-aperture decomposition is performed on complex SAR images to obtain a series of sub-aperture images, and the Stacked Convolutional Auto-Encoders (SCAE) are applied to extract the sub-aperture features from the sub-aperture images. Finally, the sub-aperture and the full-aperture features are concatenated to form the joint features, which are used to accomplish target discrimination. The accuracy of the method proposed in this paper is 16.32% higher than that of the approach only using the full-aperture feature on GF-3 UFS SAR images.
- Synthetic Aperture Radar (SAR),
- Deep learning,
- Sub-aperture feature learning,
- Ship target discrimination,
- Multichannel false-target

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References(29)

References

[1]	杜兰, 王兆成, 王燕, 等. 复杂场景下单通道SAR目标检测及鉴别研究进展综述[J]. 雷达学报, 2020, 9(1): 34–54. doi: 10.12000/JR19104 DU Lan, WANG Zhaocheng, WANG Yan, et al. Survey of research progress on target detection and discrimination of single-channel SAR images for complex scenes[J]. Journal of Radars, 2020, 9(1): 34–54. doi: 10.12000/JR19104
[2]	吴亮, 雷斌, 韩冰, 等. 卫星姿态误差对多通道SAR成像质量的影响[J]. 测绘通报, 2015, (1): 124–130. doi: 10.13474/j.cnki.11-2246.2015.0026 WU Liang, LEI Bin, HAN Bing, et al. The impact of satellite attitude error on multi-channel SAR image quality[J]. Bulletin of Surveying and Mapping, 2015, (1): 124–130. doi: 10.13474/j.cnki.11-2246.2015.0026
[3]	张双喜, 乔宁, 邢孟道, 等. 多普勒频谱模糊情况下的星载方位向多通道高分宽幅SAR-GMTI杂波抑制方法[J]. 雷达学报, 2020, 9(2): 295–303. doi: 10.12000/JR20005 ZHANG Shuangxi, QIAO Ning, XING Mengdao, et al. A novel clutter suppression approach for the space-borne multiple channel in the azimuth high-resolution and wide-swath SAR-GMTI system with an ambiguous Doppler spectrum[J]. Journal of Radars, 2020, 9(2): 295–303. doi: 10.12000/JR20005
[4]	ZHANG Shuangxi, XING Mengdao, XIA Xianggen, et al. Multichannel HRWS SAR imaging based on range-variant channel calibration and multi-Doppler-direction restriction ambiguity suppression[J]. IEEE Transactions on Geoscience and Remote Sensing, 2014, 52(7): 4306–4327. doi: 10.1109/TGRS.2013.2281329
[5]	PAN Zongxu, LIU Lei, QIU Xiaolan, et al. Fast vessel detection in Gaofen-3 SAR images with ultrafine strip-map mode[J]. Sensors, 2017, 17(7): 1578. doi: 10.3390/s17071578
[6]	DI MARTINO G, IODICE A, RICCIO D, et al. Filtering of azimuth ambiguity in stripmap synthetic aperture radar images[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2014, 7(9): 3967–3978. doi: 10.1109/JSTARS.2014.2320155
[7]	温雪娇, 仇晓兰, 尤红建, 等. 高分辨率星载SAR起伏运动目标精细聚焦与参数估计方法[J]. 雷达学报, 2017, 6(2): 213–220. doi: 10.12000/JR17005 WEN Xuejiao, QIU Xiaolan, YOU Hongjian, et al. Focusing and parameter estimation of fluctuating targets in high resolution spaceborne SAR[J]. Journal of Radars, 2017, 6(2): 213–220. doi: 10.12000/JR17005
[8]	WEN Xuejiao, QIU Xiaolan, and YOU Hongjian. Focusing and parameter estimating of fluctuating target in high resolution spaceborne SAR[C]. 2016 CIE International Conference on Radar, Guangzhou, China, 2016: 1–5. doi: 10.1109/RADAR.2016.8059537.
[9]	REN Shaoqing, HE Kaiming, GIRSHICK R, et al. Faster R-CNN: Towards real-time object detection with region proposal networks[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2017, 39(6): 1137–1149. doi: 10.1109/TPAMI.2016.2577031
[10]	LIU Wei, ANGUELOV D, ERHAN D, et al. SSD: Single shot MultiBox detector[C]. The 14th European Conference on Computer Vision, Amsterdam, Holland, 2016. doi: 10.1007/978-3-319-46448-0_2.
[11]	LI Jianwei, QU Changwen, and SHAO Jiaqi. Ship detection in SAR images based on an improved faster R-CNN[C]. 2017 SAR in Big Data Era: Models, Methods and Applications, Beijing, China, 2017: 1–6. doi: 10.1109/BIGSARDATA.2017.8124934.
[12]	KANG Miao, LENG Xiangguang, LIN Zhao, et al. A modified faster R-CNN based on CFAR algorithm for SAR ship detection[C]. 2017 International Workshop on Remote Sensing with Intelligent Processing, Shanghai, China, 2017: 1–4. doi: 10.1109/RSIP.2017.7958815.
[13]	LIU Lei, CHEN Guowei, PAN Zongxu, et al. Inshore ship detection in SAR images based on deep neural networks[C]. 2018 IEEE International Geoscience and Remote Sensing Symposium, Valencia, Spain, 2018: 25–28. doi: 10.1109/IGARSS.2018.8519555.
[14]	ZHANG Fan, WANG Yunchong, NI Jun, et al. SAR target small sample recognition based on CNN cascaded features and AdaBoost rotation forest[J]. IEEE Geoscience and Remote Sensing Letters, 2020, 17(6): 1008–1012. doi: 10.1109/LGRS.2019.2939156
[15]	LENG Xiangguang, JI Kefeng, ZHOU Shilin, et al. Ship detection based on complex signal kurtosis in single-channel SAR imagery[J]. IEEE Transactions on Geoscience and Remote Sensing, 2019, 57(9): 6447–6461. doi: 10.1109/TGRS.2019.2906054
[16]	LENG Xiangguang, JI Kefeng, ZHOU Shilin, et al. Discriminating ship from radio frequency interference based on noncircularity and non-gaussianity in sentinel-1 SAR imagery[J]. IEEE Transactions on Geoscience and Remote Sensing, 2019, 57(1): 352–363. doi: 10.1109/TGRS.2018.2854661
[17]	ZHANG Zhimian, WANG Haipeng, XU Feng, et al. Complex-valued convolutional neural network and its application in polarimetric SAR image classification[J]. IEEE Transactions on Geoscience and Remote Sensing, 2017, 55(12): 7177–7188. doi: 10.1109/TGRS.2017.2743222
[18]	HUANG Zhongling, DATCU M, PAN Zongxu, et al. Deep SAR-Net: Learning objects from signals[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2020, 161: 179–193. doi: 10.1016/j.isprsjprs.2020.01.016
[19]	TANG Jiaxin, ZHANG Fan, ZHOU Yongsheng, et al. A fast inference networks for SAR target few-shot learning based on improved siamese networks[C]. 2019 IEEE International Geoscience and Remote Sensing Symposium, Yokohama, Japan, 2019: 1212–1215. doi: 10.1109/IGARSS.2019.8898180.
[20]	OUCHI K, TAMAKI S, YAGUCHI H, et al. Ship detection based on coherence images derived from cross correlation of multilook SAR images[J]. IEEE Geoscience and Remote Sensing Letters, 2004, 1(3): 184–187. doi: 10.1109/LGRS.2004.827462
[21]	MARINO A, SANJUAN-FERRER M J, HAJNSEK I, et al. Ship detection with spectral analysis of synthetic aperture radar: A comparison of new and well-known algorithms[J]. Remote Sensing, 2015, 7(5): 5416–5439. doi: 10.3390/rs70505416
[22]	RENGA A, GRAZIANO M D, and MOCCIA A. Segmentation of marine SAR images by sublook analysis and application to sea traffic monitoring[J]. IEEE Transactions on Geoscience and Remote Sensing, 2019, 57(3): 1463–1477. doi: 10.1109/TGRS.2018.2866934
[23]	BREKKE C, ANFINSEN S N, and LARSEN Y. Subband extraction strategies in ship detection with the subaperture cross-correlation magnitude[J]. IEEE Geoscience and Remote Sensing Letters, 2013, 10(4): 786–790. doi: 10.1109/LGRS.2012.2223656
[24]	SOUYRIS J C, HENRY C, and ADRAGNA F. On the use of complex SAR image spectral analysis for target detection: Assessment of polarimetry[J]. IEEE Transactions on Geoscience and Remote Sensing, 2003, 41(12): 2725–2734. doi: 10.1109/TGRS.2003.817809
[25]	FERRO-FAMIL L, REIGBER A, POTTIER E, et al. Scene characterization using subaperture polarimetric SAR data[J]. IEEE Transactions on Geoscience and Remote Sensing, 2003, 41(10): 2264–2276. doi: 10.1109/TGRS.2003.817188
[26]	DUMITRU C O, SCHWARZ G, and DATCU M. Land cover semantic annotation derived from high-resolution SAR images[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2016, 9(6): 2215–2232. doi: 10.1109/JSTARS.2016.2549557
[27]	HUANG Zhongling, DUMITRU C O, PAN Zongxu, et al. Classification of large-scale high-resolution SAR images with deep transfer learning[J]. IEEE Geoscience and Remote Sensing Letters, 2021, 18(1): 107–111. doi: 10.1109/LGRS.2020.2965558
[28]	TerraSAR-X Basic Product Specification Document, Issue1.9[Online]. http://sss.terrasar-x.dlr.de/pdfs/TX-GS-DD-3302.pdf, 2013.
[29]	HUANG Zhongling, PAN Zongxu, and LEI Bin. What, where, and how to transfer in SAR target recognition based on deep CNNs[J]. IEEE Transactions on Geoscience and Remote Sensing, 2020, 58(4): 2324–2336. doi: 10.1109/TGRS.2019.2947634

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Multichannel False-target Discrimination in SAR Images Based on Sub-aperture and Full-aperture Feature Learning

DOI: 10.12000/JR20106 CSTR: 32380.14.JR20106