含旋转部件的动态目标特征提取方法研究
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摘要
针对含有活动部件的空中动态目标成像方法进行研究,分析活动部件对空中动态目标成像的干扰,通过自适应小波变换分离活动部件及目标,剔除活动部件对成像结果的影响;提取清晰的散射中心,然后基于逆合成孔径雷达(inverse synthetic aperture radar, ISAR)图像灰度级不连续点寻找区域边界,将目标点和背景分离,采用自适应边界收敛方法对目标区域进行轮廓特征提取,得到了良好的目标轮廓特征.所提算法不仅可剔除旋转部件对散射中心的干扰,同时可提取良好的目标ISAR特征.采用实测数据对方法进行了验证.
The imaging of dynamic object with rotating parts cannot be used for feature extraction directly. To get contour feature of the target, an effective feature extraction method is proposed. Firstly, the adaptive wavelet transform is performed to separate the signal parameters of moving parts from the target's. Then, based on the discontinuity point of image gray scale, the target is separated from the background. Finally, an adaptive boundary convergence method is used to extract the contour features of the target region, and a good contour feature is obtained. The effectiveness and stability of the proposed algorithm is verified by measured data.
The imaging of dynamic object with rotating parts cannot be used for feature extraction directly. To get contour feature of the target, an effective feature extraction method is proposed. Firstly, the adaptive wavelet transform is performed to separate the signal parameters of moving parts from the target's. Then, based on the discontinuity point of image gray scale, the target is separated from the background. Finally, an adaptive boundary convergence method is used to extract the contour features of the target region, and a good contour feature is obtained. The effectiveness and stability of the proposed algorithm is verified by measured data.
引文
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[4] 魏佳琪, 张磊, 刘宏伟, 等. 基于相位测距的宽带雷达弹道目标微动几何参数估计[J]. 电子与信息学报, 2018, 40(9): 2227-2234. WEI J Q, ZHANG L, LIU H W. Micro-motion and geometric parameters estimation of wide-band radar cone-shaped targets based on phase-derived range[J]. Journal of electronics and information technology,2018, 40(9): 2227-2234.(in Chinese)
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[6] 安成锦, 陈曾平. 基于OTSU和改进CV模型的SAR图像水域分割算法[J]. 信号处理,2011,27(2): 221-225. AN C J,CHEN Z P.SAR water segmentation based on Otsu and improved CV model[J]. Journal of signal processing, 2011,27(2): 221-225.(in Chinese)
[7] 陈凤.基于HRRP和JEM信号的雷达目标识别技术研究[D]. 西安: 西安电子科技大学, 2009. CHEN F. Research on radar target regognition based on HRRP and JEM signal[D].Xi'an: Xidian University,2009.(in Chinese)
[8] 贾守卿,江小敏, 夏明耀. 基于微多普勒特征的目标分类[J]. 电波科学学报, 2013, 28 (3):41-45. JIA S Q, JIANG X M, XIA M Y.Target classification by micro-Doppler feature[J]. Chinese journal of radio science,2013,28(3):41-45.(in Chinese)
[2] LI F J. Model-based signal processing for radar imaging of targets with complex motion[D]. Austin: University of Texas at Austin, 2002.
[3] 陈行勇. 微动目标雷达特征提取技术研究[D]. 长沙: 国防科技大学, 2006. CHEN X Y.Extraction of micro-doppler signature for radar target[D].Changsha:National University of Defense Technology,2006.(in Chinese)
[4] 魏佳琪, 张磊, 刘宏伟, 等. 基于相位测距的宽带雷达弹道目标微动几何参数估计[J]. 电子与信息学报, 2018, 40(9): 2227-2234. WEI J Q, ZHANG L, LIU H W. Micro-motion and geometric parameters estimation of wide-band radar cone-shaped targets based on phase-derived range[J]. Journal of electronics and information technology,2018, 40(9): 2227-2234.(in Chinese)
[5] 束长勇, 张生俊, 黄沛霖, 等. 基于微多普勒的空间椎体目标微动分类[J]. 北京航空航天大学学报, 2017, 43 (7): 1387-1394. SU C Y,ZHANG S J,HUANG P L,et al.Space cone targets classification by micro-doppler feature[J].Journal of Beijing University of Aeronautics and astronautics, 2017, 43 (7): 1387-1394.(in Chinese)
[6] 安成锦, 陈曾平. 基于OTSU和改进CV模型的SAR图像水域分割算法[J]. 信号处理,2011,27(2): 221-225. AN C J,CHEN Z P.SAR water segmentation based on Otsu and improved CV model[J]. Journal of signal processing, 2011,27(2): 221-225.(in Chinese)
[7] 陈凤.基于HRRP和JEM信号的雷达目标识别技术研究[D]. 西安: 西安电子科技大学, 2009. CHEN F. Research on radar target regognition based on HRRP and JEM signal[D].Xi'an: Xidian University,2009.(in Chinese)
[8] 贾守卿,江小敏, 夏明耀. 基于微多普勒特征的目标分类[J]. 电波科学学报, 2013, 28 (3):41-45. JIA S Q, JIANG X M, XIA M Y.Target classification by micro-Doppler feature[J]. Chinese journal of radio science,2013,28(3):41-45.(in Chinese)