一种联合多特征量的SAR人造微弱痕迹检测方法

doi:10.19665/j.issn1001-2400.2019.06.019

Abstract

Abstract:

When detecting the man-made weak trace like the footprints and wheel prints, a large number of false alarm areas caused by natural scenes appear in the detection results due to their low correlation, such as the vegetation and rivers. To solve this problem, this paper first gets the preliminary detection results with the Coherent Change Detection (CCD). Then by analyzing the Radar Cross Section (RCS) model of the natural scenes, it is found that the vegetation region varies much on image intensity while the river region gets a lower image intensity compared to the man-made weak trace. Based on this research, the differential and the sum of the image-pair intensity are taken as two test statistics to eliminate the vegetation and river regions from the preliminary detection results, and then a combined multi-feature method is proposed for man-made weak trace detection. The proposed method can reduce the false alarm rate and lead to fine detection results by multi-features. Finally, the processing results of the millimeter wave Synthetic Aperture Radar (SAR) real data verify the efficiency of the proposed method.

Key words: synthetic aperture radar, man-made weak trace, coherent change detection

CLC Number:

TN957.51

WANG Zhihao,ZHANG Jinsong,SUN Guangcai,LI Jun,XING Mengdao. Combined multi-features method for the detection of SAR man-made weak trace[J].Journal of Xidian University, 2019, 46(6): 131-139.

Figures/Tables 9

References 20

[1]	保铮, 邢孟道, 王彤 . 雷达成像技术[M]. 1版. 北京: 电子工业出版社, 2005.
[2]	SUN G C, WU Y, YANG J , et al. Full-aperture Focusing of Very High Resolution Spaceborne-squinted Sliding Spotlight SAR Data[J]. IEEE Transactions on Geoscience and Remote Sensing, 2017,55(6):3309-3321. doi: 10.1109/TGRS.2017.2669205
[3]	BIE B W, XING M D, XIA X G , et al. A Frequency Domain Backprojection Algorithm Based on Local Cartesian Coordinate and Subregion Range Migration Correction for High-squint SAR Mounted on Maneuvering Platforms[J]. IEEE Transactions on Geoscience and Remote Sensing, 2018,56(12):7086-7101. doi: 10.1109/TGRS.2018.2848249
[4]	景国彬, 李宁, 孙光才 , 等. 联合误差估计的机载超高分辨率SAR成像[J]. 西安电子科技大学学报, 2019,46(3):1-7.
	JING Guobin, LI Ning, SUN Guangcai , et al. Very High Resolution SAR Imaging Method Combined with Motion Estimation[J]. Journal of Xidian University, 2019,46(3):1-7.
[5]	VU V T . Wavelength-resolution SAR Incoherent Change Detection Based on Image Stack[J]. IEEE Geoscience and Remote Sensing Letters, 2017,14(7):1012-1016. doi: 10.1109/LGRS.2017.2692255
[6]	PREISS M, STACY N J S . Coherent Change Detection: Theoretical Description and Experimental Result: DSTO-TR-1851[R]. Edinburgh: Defense Science and Technology Organization, 2006.
[7]	JUNG J, KIM D J, LAVALLE M , et al. Coherent Change Detection Using InSAR Temporal Decorrelation Model: a Case Study for Volcanic Ash Detection[J]. IEEE Transactions on Geoscience and Remote Sensing, 2016,54(10):5765-5775. doi: 10.1109/TGRS.2016.2572166
[8]	NEWEY M, BENITZ G, KOGON S . A Generalized Likelihood Ratio Test for SAR CCD[C]//Proceedings of the 2012 Asilomar Conference on Signals, Systems and Computers. Washington: IEEE Computer Society, 2012: 1727-1730.
[9]	赵军香, 梁兴东, 李焱磊 . 一种基于似然比统计量的SAR相干变化检测[J]. 雷达学报, 2017,6(2):186-194.
	ZHAO Junxiang, LIANG Xingdong, LI Yanlei . Change Detection in SAR CCD Based on the Likelihood Change Statistics[J]. Journal of Radars, 2017,6(2):186-194.
[10]	TOUZI R, LOPES A . Statistics of the Stokes Parameters and of the Complex Coherence Parameters in One-look and Multilook Speckle Fields[J]. IEEE Transactions on Geoscience and Remote Sensing, 1996,34(2):519-531. doi: 10.1109/36.485128
[11]	LEE K W, KIM H C, KIM B , et al. Design of SAR Image Feature Detector for Small-scaled Coherent Change Detection[C]//Proceedings of the 2016 International Geoscience and Remote Sensing Symposium. Piscataway: IEEE, 2016: 2344-2347.
[12]	MONTI-GUARNIERI A V, BROVELLI M A, MANZONI M , et al. Coherent Change Detection for Multipass SAR[J]. IEEE Transactions on Geoscience and Remote Sensing, 2018,56(11):6811-6822. doi: 10.1109/TGRS.2018.2843560
[13]	冀广宇, 董勇伟, 卜运成 , 等. 基于目标相干性表征差异的多波段SAR相干变化检测方法[J]. 雷达学报, 2018,7(4):455-464.
	JI Guangyu, DONG Yongwei, BU Yuncheng , et al. Multi-band SAR Coherent Change Detection Method Based on Coherent Representation Differences of Targets[J]. Journal of Radars, 2018,7(4):455-464.
[14]	CHA M, PHILLIPS R D, WOLFE P J . Combined Intensity and Coherent Change Detection for Synthetic Aperture Radar[C]//Proceedings of the 2014 IEEE International Conference on Acoustics, Speech and Signal Processing. Piscataway: IEEE, 2014: 8120-8123.
[15]	TOUZI R, LOPES A, BRUNIQUEL J , et al. Coherence Estimation for SAR Imagery[J]. IEEE Transactions on Geoscience and Remote Sensing, 1999,37(1):135-149. doi: 10.3390/s19143073 pmid: 31336806
[16]	CHA M, PHILLIPS R, WOLFE P J . Test Statistics for Synthetic Aperture Radar Coherent Change Detection[C]//Proceedings of the 2012 IEEE Statistical Signal Processing Workshop. Washington: IEEE Computer Society, 2012: 856-859.
[17]	连晓锋, 朱振波, 汪先超 , 等. 复杂杂波背景下机载预警雷达探测性能分析[J]. 舰船电子对抗, 2015,38(5):19-24.
	LIAN Xiaofeng, ZHU Zhenbo, WANG Xianchao , et al. Detection Performance Analysis of AEW Radar under Complex Clutter Background[J]. Shipboard Electronic Countermeasure, 2015,38(5):19-24.
[18]	ZEBKER H A, VILLASENOR J . Decorrelation in Interferometric Radar Echoes[J]. IEEE Transactions on Geoscience and Remote Sensing, 1992,30(5):950-959. doi: 10.1109/36.175330
[19]	ULABY F T . Vegetation Clutter Model[J]. IEEE Transactions on Antennas and Propagation, 1980,28(4):538-545. doi: 10.1371/journal.pone.0182824 pmid: 28817631
[20]	GARCIA-GARCIA A, ORTS-ESCOLANO S, OPREA S , et al. A Review on Deep Learning Techniques Applied to Semantic Segmentation[J/OL]. [2019-03-16]. https://arXiv.org/format/1704.06857.

指标	方法	人造痕迹区域	虚警区域1	虚警区域2	虚警区域3	虚警区域4
准确率	传统相干变化检测法	38.28
准确率	文中方法	54.85
虚警率	传统相干变化检测法	16.57	97.55	89.62	48.49	38.80
虚警率	文中方法	5.80	8.87	11.21	17.70	14.47

Combined multi-features method for the detection of SAR man-made weak trace

RichHTML

PDF (PC)

Like

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 9

References 20

Related Articles 15

Metrics

Comments

Recommended 10

[1]	WANG Xin,CHANG Guiqing,CHI Chenchen. Separation and imaging of the anisotropic scattering targets in the wide-angle SAR [J]. Journal of Xidian University, 2021, 48(2): 109-116.
[2]	LU Jinwen,YAN Hua,YIN Hongcheng,ZHANG Lei,DONG Chunzhu. Edge diffraction correction for 3D scattering center modeling based on the shooting and bouncing ray technique [J]. Journal of Xidian University, 2021, 48(2): 117-124.
[3]	TAO Yi,DING Li. Method for digital IQ frequency-domain calibration based on conjugate symmetry [J]. Journal of Xidian University, 2021, 48(2): 181-189.
[4]	HU Liping,YAN Hua,ZHONG Weijun,YIN Hongcheng,WANG Chao. Three-dimensional scattering center modeling and a fast SAR simulation method for ship targets [J]. Journal of Xidian University, 2021, 48(2): 72-83.
[5]	DUAN Chongdi,HAN Chaolei,YANG Zhiwei,ZHANG Qingjun. Inshore ambiguity clutter suppression method aided by clutter classification [J]. Journal of Xidian University, 2021, 48(2): 64-71.
[6]	YANG Jun,ZHOU Fang. Ultra-high resolution imaging method for the distributed small satellite MIMO-SAR [J]. Journal of Xidian University, 2021, 48(2): 99-108.
[7]	YANG Lei,YUE Yunze,LI Pucheng,ZHANG Tao,YANG Huan. Sparse representation of large dynamic range SAR imaging for multiple ground moving targets [J]. Journal of Xidian University, 2019, 46(5): 31-40.
[8]	GUO Rui,ZANG Bo,PENG Shuming,XING Mengdao. Extraction of features of the urban high-rise building from high resolution InSAR data [J]. Journal of Xidian University, 2019, 46(4): 137-143.
[9]	ZENG Chuangzhan,ZHU Weigang,JIA Xin. Sparse-aperture ISAR imaging algorithm [J]. Journal of Xidian University, 2019, 46(3): 123-129.
[10]	LIANG Yi, LI Qingqing, SUN Kun, DANG Yanfeng, DING Jinshan. New method for missile positioning based on SAR scene matching [J]. Journal of Xidian University, 2018, 45(6): 1-6.
[11]	SUN Chen, CHENG Liye. Spatial sensing matrix learning for PolSAR image classification [J]. Journal of Xidian University, 2018, 45(6): 92-98.
[12]	LIU Jiange, MU Dejun. Novel sea ice edge detection method in SAR imagery [J]. Journal of Xidian University, 2018, 45(6): 106-111.
[13]	WANG Yuekun;SUO Zhiyong;LI Zhenfang;ZHANG Jinqiang;ZHANG Qingjun. Improved CS imaging algorithm for the GEO-LEO BiSAR system [J]. Journal of Xidian University, 2018, 45(5): 50-56+196.
[14]	XU Qiang;LI Wei;ZHAN Ronghui;ZOU Kun. Improved algorithm for SAR target recognition based on the convolutional neural network [J]. Journal of Xidian University, 2018, 45(5): 177-183.
[15]	HUANG Yong;LIU Fang. Detecting water bridge in SAR images via a scene semantic algorithm [J]. Journal of Xidian University, 2018, 45(4): 40-44.