A moving ship tracking method based on long time interval sequential SAR images

doi:10.7523/j.issn.2095-6134.2021.05.008

Abstract

Abstract: Aiming at solving the difficult problem of tracking moving ships, which is caused by their great position variation in long time interval sequential SAR images, a matching tracking method combining track initiation and image feature is proposed. Firstly, the ships are detected from the SAR image to obtain the image slices and extract the ships' image features and spatial position information. Then, ships at different times are correlated to form multiple candidate trajectories according to the constraints of velocity and acceleration. Finally, ship trajectories are screened out based on the minimum difference principle of feature matching to realize moving ship tracking. The effectiveness of the proposed method is verified by simulation experiments and airborne sequential SAR images processing analysis.

Key words: synthetic aperture radar, sequential images, ship tracking

CLC Number:

TN957.52

LIU Yujie, QI Xiangyang. A moving ship tracking method based on long time interval sequential SAR images[J]. Journal of University of Chinese Academy of Sciences, 2021, 38(5): 642-648.

References

[1] Cumming I G, Wong F H. Digital signal processing of synthetic aperture radar data:algorithms and implementation[M]. Norwood, MA:Artech House, 2005:1-19.
[2] 吴琨. 机载广域监视系统动目标跟踪及其应用[D]. 北京:中国科学院大学,2014.
[3] 邢相薇. HRWS SAR图像舰船目标监视关键技术研究[D]. 长沙:国防科学技术大学,2014.
[4] Iervolino P. Ship detection with SAR:modelling, designing and real data validation[D]. Guildford:University of Surrey, 2016.
[5] Ai J, Yang X, Song J, et al. An adaptively truncated clutter-statistics-based two-parameter CFAR detector in SAR imagery[J]. IEEE Journal of Oceanic Engineering, 2017, 43(1):267-279.
[6] Kwok R, Curlander J C, McConnell R, et al. An ice-motion tracking system at the Alaska SAR facility[J]. IEEE Journal of Oceanic Engineering, 1990, 15(1):44-54.
[7] 汤宏权. 基于合成孔径雷达图像的目标跟踪与识别[D]. 长沙:中南大学,2009.
[8] 汪洪桥, 蔡艳宁, 付光远, 等. 基于图像序列的地面慢动多目标识别与跟踪[J].激光与光电子学进展,2016,53(5):253-261.
[9] Hu M K. Visual pattern recognition by moment invariants[J]. Information Theory, IRE Transactions on, 1962, 8(2):179-187.
[10] Lowe D G. Distinctive image features from scale-invariant keypoints[J]. International Journal of Computer Vision, 2004, 60(2):91-110.
[11] Dellinger F, Delon J, Gousseau Y, et al. SAR-SIFT:a SIFT-like algorithm for SAR images[J]. IEEE Transactions on Geoscience and Remote Sensing, 2015, 53(1):453-466.
[12] Lin H, Song S, Yang J. Ship classification based on MSHOG feature and task-driven dictionary learning with structured incoherent constraints in SAR images[J]. Remote Sensing, 2018, 10(2):190.
[13] 吴俊. 基于高分辨率SAR图像的舰船目标分类识别研究[D]. 杭州:浙江大学,2018.
[14] Kreithen D E, Halversen S D, Owirka G J. Discriminating targets from clutter[J]. The Lincoln Laboratory Journal, 1993, 6(1):25-52.
[15] Xing X, Ji K, Zou H, et al. Ship classification in TerraSAR-X images with feature space based sparse representation[J]. IEEE Geoscience and Remote Sensing Letters, 2013, 10(6):1562-1566.
[16] Lang H, Zhang J, Zhang X, et al. Ship classification in SAR image by joint feature and classifier selection[J]. IEEE Geoscience and Remote Sensing Letters, 2016, 13(2):212-216.
[17] 张传宾. 强杂波下多目标航迹起始算法研究[D]. 哈尔滨:哈尔滨工程大学,2018.
[18] Huang L, Liu B, Li B, et al. OpenSARShip:a dataset dedicated to Sentinel-1 ship interpretation[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2017, PP(99):1-14.
[19] 潘志刚, 潘卓, 曹舸. 机载SAR图像无控制点直接定位方法[J].中国科学院大学学报,2015,32(4):536-541.