宽带雷达目标极化特征提取与识别研究
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摘要
雷达目标识别是现代雷达对目标实现定位、测量及辨识所亟需解决的重要研究课题,但由于问题本身的复杂性,至今仍无满意的解决方法。高分辨和全极化的结合被认为是雷达目标识别最具前景的研究方向之一,同时高分辨全极化雷达也成为现代雷达发展的重要方向。本文针对高分辨全极化雷达体制,深入开展了宽带雷达目标极化特征提取与识别的研究工作,主要内容包括基于极化目标分解的宽带雷达目标特征提取与识别、全极化散射中心参数估计、基于全极化散射中心分布的宽带雷达目标特征提取与识别等,具体安排如下:
第一章阐述了宽带雷达目标极化特征提取及识别研究的意义及现状,并给出本文主要研究工作简介。
第二章介绍了雷达目标极化散射特性的表征方式,提出一种结合极化目标分解和散射中心估计的雷达目标极化散射特性分析方法,暗室实测数据分析结果表明该方法能有效揭示目标的散射机理。
第三章在分析目标全极化高分辨距离像特性以及提取极化散射矩阵的基础上,首先利用Krogager分解、Cameron分解和Cloude分解从雷达目标全极化高分辨距离像中提取三种极化特征,并设计了一种基于极化特征的目标识别流程,最后通过两组舰船目标电磁软件计算数据的识别实验检验极化特征的识别性能。与基于单极化高分辨距离像特征的识别性能相比较表明引入全极化信息能有效提高目标识别性能。
第四章首先根据不同极化通道下目标同一散射中心位置一致性的特点,研究了基于酉ESPRIT的全极化散射中心参数估计问题。相对于常规的分极化通道散射中心单独估计方法,该方法只需一次运算就可估计出所有参数,估计的精度较高,而且避免了传统方法后续的散射中心筛选、配对等工作,极大地降低了运算量,提高了数据处理的效率。其次,鉴于舰船目标散射中心分布的稀疏性差异,提出了一种基于散射中心分布稀疏度特征的舰船目标识别方法,仿真实验结果表明,该特征具有良好的识别性能,验证了该方法的合理有效。
第五章对本文内容进行系统总结,并对下一步的工作进行了展望。
Radar target recognition is an important problem needed to be solved urgently for modern radar to implement target position, measurement and recognition. However, because of the complexity of the problem itself, there is still no satisfying solution. The combination of high resolution and full polarization is considered as the one of the most promising approach to solve the problem, and thus high-resolution fully polarimetric radar is also becoming an important direction of modern radar development. In this dissertation, wideband radar target polarimetric features extraction and recognition for the high-resolution fully polarimetric radar system is discussed in depth, mainly including fully polarimetric scattering center parameter estimation, wideband radar target polarimetric feature extraction and recognition based on the polarimetric target decomposition and distribution of scattering centers. The main work in this dissertation is organized as follows:
The first chapter introduces the significance and status of wideband radar target polarimetric feature extraction and recognition, and gives the work profile of this paper.
The second chapter describes the characterization polarimetric scattering characteristics of radar target , and a method combinating polarimetric target decomposition and scattering centers estimation is proposed to analyze polarimetric scattering characteristics of radar target. This method is validated by real data measured in anechoic chamber.
The third chapter firstly introduces the characteristics of fully high range resolution profile(HRRP) and polarimetric target decomposition theory. Subsequently, it applies the Krogager decomposition, Cameron decomposition and Cloude decomposition to the fully HRRP of radar target to extract three types of polarimetric features, based on which a target recognition procedure is designed; Finally, two simulation experiments on data of two groups of ships calculated through the electromagnetic software are carried out to test the effectiveness of these polarimetric features. Compared to the recognition performance of the feature extracted from single polarization HRRP, the method in this paper effectively improves the recognition performance by employing fully polarimetric information.
The fourth chapter firstly works on fully polarimetric scattering center parameter estimation using Unitary ESPRIT according to the location consistency of scattering centers in different polarization channel. Unlike the conventional scattering center estimation under single polarization channel, the proposed method can not only estimate all parameters in one operation with high estimation accuracy, but also avoid such problems as screening and matching of scattering centers, which greatly reduces the computation burden and improves the processing efficiency. Secondly, for ship targets, given the sparseness differences of scattering centers distribution, a target recognition method based on sparse degree of scattering centers is put forward. In fact, it is observed from simulation experiment results that the feature of sparse degree can provide good recognition performance, which proves that the method is reasonable and effective.
The last chapter presents a conclusion of this dissertation and a description of the future work.
第一章阐述了宽带雷达目标极化特征提取及识别研究的意义及现状,并给出本文主要研究工作简介。
第二章介绍了雷达目标极化散射特性的表征方式,提出一种结合极化目标分解和散射中心估计的雷达目标极化散射特性分析方法,暗室实测数据分析结果表明该方法能有效揭示目标的散射机理。
第三章在分析目标全极化高分辨距离像特性以及提取极化散射矩阵的基础上,首先利用Krogager分解、Cameron分解和Cloude分解从雷达目标全极化高分辨距离像中提取三种极化特征,并设计了一种基于极化特征的目标识别流程,最后通过两组舰船目标电磁软件计算数据的识别实验检验极化特征的识别性能。与基于单极化高分辨距离像特征的识别性能相比较表明引入全极化信息能有效提高目标识别性能。
第四章首先根据不同极化通道下目标同一散射中心位置一致性的特点,研究了基于酉ESPRIT的全极化散射中心参数估计问题。相对于常规的分极化通道散射中心单独估计方法,该方法只需一次运算就可估计出所有参数,估计的精度较高,而且避免了传统方法后续的散射中心筛选、配对等工作,极大地降低了运算量,提高了数据处理的效率。其次,鉴于舰船目标散射中心分布的稀疏性差异,提出了一种基于散射中心分布稀疏度特征的舰船目标识别方法,仿真实验结果表明,该特征具有良好的识别性能,验证了该方法的合理有效。
第五章对本文内容进行系统总结,并对下一步的工作进行了展望。
Radar target recognition is an important problem needed to be solved urgently for modern radar to implement target position, measurement and recognition. However, because of the complexity of the problem itself, there is still no satisfying solution. The combination of high resolution and full polarization is considered as the one of the most promising approach to solve the problem, and thus high-resolution fully polarimetric radar is also becoming an important direction of modern radar development. In this dissertation, wideband radar target polarimetric features extraction and recognition for the high-resolution fully polarimetric radar system is discussed in depth, mainly including fully polarimetric scattering center parameter estimation, wideband radar target polarimetric feature extraction and recognition based on the polarimetric target decomposition and distribution of scattering centers. The main work in this dissertation is organized as follows:
The first chapter introduces the significance and status of wideband radar target polarimetric feature extraction and recognition, and gives the work profile of this paper.
The second chapter describes the characterization polarimetric scattering characteristics of radar target , and a method combinating polarimetric target decomposition and scattering centers estimation is proposed to analyze polarimetric scattering characteristics of radar target. This method is validated by real data measured in anechoic chamber.
The third chapter firstly introduces the characteristics of fully high range resolution profile(HRRP) and polarimetric target decomposition theory. Subsequently, it applies the Krogager decomposition, Cameron decomposition and Cloude decomposition to the fully HRRP of radar target to extract three types of polarimetric features, based on which a target recognition procedure is designed; Finally, two simulation experiments on data of two groups of ships calculated through the electromagnetic software are carried out to test the effectiveness of these polarimetric features. Compared to the recognition performance of the feature extracted from single polarization HRRP, the method in this paper effectively improves the recognition performance by employing fully polarimetric information.
The fourth chapter firstly works on fully polarimetric scattering center parameter estimation using Unitary ESPRIT according to the location consistency of scattering centers in different polarization channel. Unlike the conventional scattering center estimation under single polarization channel, the proposed method can not only estimate all parameters in one operation with high estimation accuracy, but also avoid such problems as screening and matching of scattering centers, which greatly reduces the computation burden and improves the processing efficiency. Secondly, for ship targets, given the sparseness differences of scattering centers distribution, a target recognition method based on sparse degree of scattering centers is put forward. In fact, it is observed from simulation experiment results that the feature of sparse degree can provide good recognition performance, which proves that the method is reasonable and effective.
The last chapter presents a conclusion of this dissertation and a description of the future work.
引文
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[29]汪洋,鲁加国,张长耀.基于Krogager分解和SVM的极化SAR图像分类[J].遥感技术与应用, 2007, 22(1): 70~74.
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[2] Nebabin V. G. Methods and techniques of radar recognition[M]. Boston: Artech House, 1997.
[3]王晓丹,王积勤.雷达目标识别技术综述[J].现代雷达, 2003, 25(5): 22~26.
[4]庄钊文,肖顺平,王雪松.雷达极化信息处理及应用[M].北京:国防工业出版社, 1999.
[5]从田力主编.世界天基雷达技术发展概况[M].北京:国防工业出版社, 2007.
[6] Eaves J. L, Reedy E. K.编.卓荣邦,杨士毅等译.现代雷达原理[M].北京:电子工业出版社, 1999.
[7]郭雷.宽带雷达目标极化特征提取与核方法识别研究[D].长沙:国防科技大学博士学位论文, 2009.
[8]李丽亚.宽带雷达目标识别技术研究[D].西安:西安电子科技大学博士学位论文, 2009.
[9]代大海.极化雷达成像及目标特征提取研究[D].长沙:国防科技大学博士学位论文, 2008.
[10]杜兰.雷达高分辨距离像目标识别方法研究[D].西安:西安电子科技大学博士学位论文, 2007.
[11]袁莉.基于高分辨距离像的雷达目标识别方法研究[D].西安:西安电子科技大学博士学位论文, 2007.
[12] Bickel S H. Some invariant properties of the polarization scattering matrix[C]. Proceedings of IEEE, 1965, 53(8): 1070~1072.
[13] Ferrazzoli P, Paloscia S, Pampaloni P, et al. The potential of multifrequency polarimetric SAR in assessing agricultural and arborous biomass[J]. IEEE Transactions on Geoscience and Remote Sensing, 1997, 35(1): 5~17.
[14] Pellizzeri T M, Lombardo P. Model-based processing of multifrequency polarimetric SAR images of urban areas[C]. Proceedings of GRSS/ISPRS Joint Workshop on Data Fusion and Remote Sensing over Urban Areas, 2003: 47~51.
[15] Lombardo P. Optimal classification of polarimetric SAR images using segmentation[C]. Proceedings of IEEE International Radar Conference, Long Beach, California, 2002: 8~13.
[16]李盾,肖顺平,王雪松.基于回波趋向伪本征极化特性的目标识别研究[J].电子学报, 1999, 27(9): 1~4.
[17]肖顺平,庄钊文,王雪松,郭桂蓉.目标动态极化结构特征提取与识别[J].电子学报, 1996, 26(3): 48~52.
[18]肖顺平,郭桂蓉,王雪松.基于极化频率稳定度的目标识别[J].现代雷达, 1995, 17(5): 1~7.
[19]肖怀铁.宽带极化毫米波雷达目标特征信号测量与识别算法研究[D].长沙:国防科技大学博士学位论文, 2000.
[20] Li H J, Lane R Y. Utilization of multiple polarization data for aerospace target identification[J]. IEEE Transaction on Antennas and Propagation, 1995, 3(12): 110~112.
[21]曹向海,刘宏伟,吴顺君.多极化多特征融合的雷达目标识别研究[J].系统工程与电子技术, 2008, 30(2): 261~264.
[22] Foo B Y, Boerner W M. Basic monostatic polarimetric broadband target scattering analysis required for high resolution polarimetric radar target downrange crossrange imaging of airbone scatterers[R]. Measurement, processing and analysis of radar target signature, USA, The Ohio state university, September, 1985.
[23] Huynen J R. Phenomenological theory of radar targets[D]. Delft, The Netherlands: Technical University of Delft, 1970.
[24] Cloude S R, Pottier E. A review of target decomposition theorems in radar polarimetry[J]. IEEE Transactions on Geoscience and Remote Sensing, 1996, 34(2): 498~518.
[25] van Zyl J J. Unsupervised classification of scattering behavior using radar polarimetry data[J]. IEEE Transactions on Geoscience and Remote Sensing, 1989, 27(1): 36~45.
[26] Belhadj Z, Benazza A, and Hidoussi N. Classification of radar images in polarimetric remote sensing[C]. Proc. International Conference on Image Processing, Seattle, Washington, USA, July 1998: 574~577.
[27]曹芳,洪文,吴一戎.基于Cloude-Pottier目标分解和聚合的层次聚类算法的全极化SAR数据的非监督分类算法[J].电子学报, 2008, 36(3): 543~546.
[28]陈劲松,邵芸,李震.基于目标分解理论的全极化SAR图像神经网路分类方法[J].中国图像图形学报, 2004, 9(5): 552~556.
[29]汪洋,鲁加国,张长耀.基于Krogager分解和SVM的极化SAR图像分类[J].遥感技术与应用, 2007, 22(1): 70~74.
[30]汪洋,鲁加国,张长耀.基于Cameron分解和SVM的极化SAR图像分类[J].计算机工程与应用, 2006,42(36): 17~19,22.
[31] Lee J S, Grunes M R. Unsupervised terrain classification preserving polarimetricscattering characteristic. IEEE Transaction on Geoscience and Remote Sensing, 2004, 42(4): 722~731.
[32] Touzi R, Charbonneau F, Hawkins R. K, et al. Ship—sea contrast optimization when using polarimetric SARs[J]. IEEE International Geoscience and Remote Sensing Symposium, IGARSS 01. Sydney: 2001.
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