Modeling of Micromotion and Analysis of Properties of Rigid Marine Targets
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摘要: 微多普勒描述了海面目标运动的精细特征,成为区分海杂波和目标的有用特征之一,有助于提高雷达目标探测和识别能力。该文以对海观测雷达为平台,建立了海杂波中微动目标雷达回波模型。首先,简要回顾了微动和微多普勒效应的定义,归纳总结出微多普勒效应的内涵和实质,并给出了海面刚体目标的微动特征分类。然后,根据观测时长将模型分为距离单元内微动目标回波模型和长时间微动目标观测模型;根据海面微动目标的运动形式,将模型分为非匀速平动目标回波模型和3轴转动目标回波模型。最后,采用雷达实测数据分析微动特征并验证模型的有效性。Abstract: As one of the most useful phenomena for separating sea clutter and marine targets, micro-Doppler (m-D) describes the refined motion characteristics of a marine target and helps to improve the abilities of radar detection and recognition. In this study, based on maritime radar, the signal model of a target with micromotion in sea clutter is described. Initially, the definitions of micromotion and m-D are briefly reviewed with a description of their details, and a classification of rigid marine targets that exhibit micromotion is introduced. Then, according to the duration of the observation time, we establish two types of signal models, i.e., in one range unit and across range unit. According to the type of motion, we establish separate signal models for non-uniform translational motion and rotational motion. Finally, the properties of micromotion are analyzed using real radar data, and the effectiveness of the established models is verified.
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Key words:
- Rigid target /
- Micro-Doppler /
- Property analysis /
- Sea clutter /
- Long-time integration
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[1] Ward K D and Watts S. Use of sea clutter models in radar design and development[J].IET Radar, Sonar Navigation, 2010, 4(2): 146-157. [2] Chen X L, Guan J, Liu N B, et al.. Detection of a low observable sea-surface target with micromotion via the Radon-linear canonical transform[J].IEEE Geoscience and Remote Sensing Letters, 2014, 11(7): 1225-1229. [3] Greco M, Stinco P, Gini F, et al.. Impact of sea clutter nonstationarity on disturbance covariance matrix estimation and CFAR detector performance[J].IEEE Transactions on Aerospace and Electronic Systems, 2010, 46(3): 1502-1513. [4] 黄勇, 陈小龙, 关键. 实测海尖峰特性分析及抑制方法[J]. 雷达学报, 2015, 4(3): 334-342.Huang Y, Chen X L, and Guan J. Property analysis and suppression method of real measured sea spikes[J]. Journal of Radars, 2015, 4(3): 334-342. [5] Al-Ashwal W A, Woodbridge K, and Griffiths H D. Analysis of bistatic sea clutterpart I: average reflectivity[J]. IEEE Transactions on Aerospace and Electronic Systems, 2014, 50(2): 1283-1292. [6] 陈小龙, 关键, 何友. 微多普勒理论在海面目标检测中的应用及展望[J]. 雷达学报, 2013, 2(1): 123-134.Chen X L, Guan J, and He Y. Applications and prospect of micro-motion theory in the detection of sea surface target[J]. Journal of Radars, 2013, 2(1): 123-134. [7] Shui P L, Li D C, and Xu S W. Tri-feature-based detection of floating small targets in sea clutter[J]. IEEE Transactions on Aerospace and Electronic Systems, 2014, 50(2): 1416-1430. [8] Chen V C, Fayin Li, Ho S-S, et al.. Micro-Doppler effect in radar: phenomenon, model, and simulation study[J]. IEEE Transactions on Aerospace and Electronic Systems, 2006, 42(1): 2-21. [9] 罗迎, 张群, 王国正, 等. 基于复图像OMP分解的宽带雷达微动特征提取方法[J]. 雷达学报, 2012, 1(4): 361-369.Luo Y, Zhang Q, Wang G Z, et al.. Micro-motion signature extraction method for wideband radar based on complex image OMP decomposition[J]. Journal of Radars, 2012, 1(4): 361-369. [10] Chen X L, Guan J, Bao Z H, et al.. Detection and extraction of target with micro-motion in spiky sea clutter via short-time fractional Fourier transform[J]. IEEE Transactions on Geoscience and Remote Sensing, 2014, 52(2): 1002-1018. [11] Chen V C, David Tahmoush, and William J Miceli. Radar Micro-Doppler Signature: Processing and Applications[M]. UK: IET, 2014. [12] Chen X L, Guan J, Li X Y, et al.. Effective coherent integration method for marine target with micromotionvia phase differentiation and radon-Lvs distribution[J]. IET Radar, Sonar Navigation, 2015, 9(9): 1284-1295. [13] Chen X L, Guan J, Huang Y, et al.. Radon-linear canonical ambiguity function-based detection and estimation method for marine target with micromotion[J]. IEEE Transactions on Geoscience and Remote Sensing, 2015, 53(4): 2225-2240. [14] 李彦兵, 杜兰, 刘宏伟, 等. 基于微多普勒效应和多级小波分解的轮式履带式车辆分类研究[J]. 电子与信息学报, 2013, 35(4): 894-900.Li Y B, Du L, Liu H W, et al.. Study on classification of wheeled and tracked vehicles based on micro-Doppler effect and multilevel wavelet decomposition[J]. Journal of Electronics Information Technology, 2013, 35(4): 894-900. [15] Chen X L, Guan J, Liu N B, et al.. Maneuvering target detection via Radon-fractional Fourier transform-based long-time coherent integration[J]. IEEE Transactions on Signal Processing, 2014, 62(4): 939-953. [16] Wang Y. Inverse synthetic aperture radar imaging of maneuvering target based on range-instantaneous-Doppler and range-instantaneous-chirp-rate algorithms[J]. IET Radar, Sonar Navigation, 2012, 6(9): 921-928. [17] De Wind H J, Cilliers J E, and Herselman P L. Dataware: sea clutter and small boat radar reflectivity databases[J]. IEEE Signal Processing Magazine, 2010, 27(2): 145-148.
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