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基于分数阶傅里叶变换的弹载SAR成像算法

陈勇 赵惠昌 陈思 张淑宁

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基于分数阶傅里叶变换的弹载SAR成像算法

陈勇, 赵惠昌, 陈思, 张淑宁

Imaging algorithm for missile-borne SAR using the fractional Fourier transform

Chen Yong, Zhao Hui-Chang, Chen Si, Zhang Shu-Ning
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  • 针对弹载合成孔径雷达(SAR)回波信号的多普勒参数随斜距变化大及传统脉冲压缩成像算法分辨率低的问题,本文提出了一种基于分数阶傅里叶变换(FrFT)的弹载SAR成像算法. 首先建立弹载SAR末制导阶段回波信号模型,然后通过局部最优处理来测量回波信号的调频率,并以此计算FrFT的最优阶次,在最优阶次下分别对回波信号进行距离向和方位向的FrFT,从而得到成像区域的SAR图像,最后分别采用传统脉冲压缩成像算法与本文基于FrFT的成像算法进行仿真和实测对比实验. 实验结果表明,该算法能够对目标区域精确成像;由于在成像处理过程中,对每个距离向和方位向的回波信号进行独立的局部最优处理,因此该算法更适应于弹载SAR的非线性飞行轨迹,大大提高了弹载SAR的成像性能. 该研究成果在目标探测与识别,精确制导等领域中具有重要的应用价值.
    Since the Doppler parameters vary according to the slant distance, the resolution is lower when using an imaging algorithm of traditional pulse compression in processing raw echo data of the missile-borne synthetic aperture radar (SAR). Moreover, an algorithm is proposed to solve these problems, which is based on the fractional Fourier transform (FrFT) for missile-borne SAR imaging. Firstly, an echo signal model is built for the terminal guidance stage of the missile-borne SAR. Secondly, the chirp rate of the echo signal is measured through the local optimum processing and obtains the optimum angles for the FrFT, and then the entire SAR image can be obtained by using FrFT with the optimum azimuth angles and operating range. Finally, the performances of the algorithms are assessed using simulated and real Radarsat-1 data sets. Results confirm that the FrFT-based missile-borne SAR processing methods can provide enhanced resolution that yields both lower-side lobes effects and improved target detection. The method introduced in this paper has important theoretical significance in detection and recognition of military targets and for precision guidance.
    • 基金项目: 国家自然科学基金(批准号:61301216)和江苏省普通高校研究生科研创新计划(批准号:CXZZ130206)资助的课题.
    • Funds: Project supported by the National Natural Science Foundation of China (Grant No. 61301216), and the Research and Innovation Plan for Graduate Students of Jiangsu Higher Education Institutions, China (Grant No. CXZZ130206).
    [1]

    Ji W J, Tong C M 2012 Acta Phys. Sin. 61 160301 (in Chinese)[姬伟杰, 童创明 2012 物理学报 61 160301]

    [2]

    Liu G G, Zhang L R, Liu N, Chen G F, Zhang Y 2013 IEEE Geosci Remote S. 10 342

    [3]

    Ji W J, Tong C M 2013 Chin. Phys. B 22 020301

    [4]

    Wu Y G, Tao M D 2006 Chin. Phys. B 15 1137

    [5]

    Yan Y, Zhou Y Q, Li C S, Xu L X 2002 J. Electron. Inf. Tech. 24 1932 (in Chinese) [燕英, 周荫清, 李春升, 许丽香 2002 电子与信息学报 24 1932]

    [6]

    Yu G M, Deng H T, Zhang C Y, Wu S J 2006 J. Syst. Eng. Electron. 28 997 (in Chinese) [俞根苗, 邓海涛, 张长耀, 吴顺君 2006 系统工程与电子技术 28 997]

    [7]

    Fang L L, Wang Y F 2008 J. Electron. Inf. Tech. 30 1316 (in Chinese) [房丽丽, 王岩飞 2008 电子与信息学报 30 1316]

    [8]

    Zhou P, Xiong T, Zhou S, Li Y C, Xing M D 2011 J. Electron. Inf. Tech. 33 622 (in Chinese) [周鹏, 熊涛, 周松, 李亚超, 邢孟道 2011 电子与信息学报 33 622]

    [9]

    Zhou S, Bao M, Zhou P, Xing M D, Bao Z 2011 J. Electron. Inf. Tech. 33 1420 (in Chinese) [周松, 包敏, 周鹏, 邢孟道, 保铮 2011 电子与信息学报 33 1420]

    [10]

    Almeida L B 1994 IEEE Trans. Signal Proc. 42 3084

    [11]

    Ozaktas H M, O Arikan, Kutay M A, Bozdagt G 1996 IEEE Trans. Signal Proc. 44 2141

    [12]

    Shinde S, Gadre V 2001 IEEE Trans. Signal Proc. 49 2545

    [13]

    Amein A S, Soraghan J J 2005 IEEE Trans. Signal Proc Let. 12 705

    [14]

    Amein A S, Soraghan J J 2007 IEEE Trans. Signal Proc. 55 4162

    [15]

    Clemente C, Soraghan J J 2012 IET Signal Processing. 6 503

    [16]

    Deng B, Li X, Wang H Q, Qin Y L, Wang J T 2011 IEEE Geosci. Remote S. 8 44

    [17]

    Chen S, Zhao H C, Zhang S N Chen Y 2013 Acta Phys. Sin. 62 218405 (in Chinese) [陈思, 赵惠昌, 张淑宁, 陈勇 2013 物理学报 62 218405]

    [18]

    Tao R, Deng B, Wang Y 2009 Fractional Fourier Transform (Beijing: Tsinghua University Press) p25 (in Chinese) [陶然, 邓兵, 王越, 2009 分数阶傅里叶变换及其应用(北京:清华大学出版社)第25 页]

    [19]

    Capus C, Brown K 2003 J. Acoust. Soc. Am. 113 3253

  • [1]

    Ji W J, Tong C M 2012 Acta Phys. Sin. 61 160301 (in Chinese)[姬伟杰, 童创明 2012 物理学报 61 160301]

    [2]

    Liu G G, Zhang L R, Liu N, Chen G F, Zhang Y 2013 IEEE Geosci Remote S. 10 342

    [3]

    Ji W J, Tong C M 2013 Chin. Phys. B 22 020301

    [4]

    Wu Y G, Tao M D 2006 Chin. Phys. B 15 1137

    [5]

    Yan Y, Zhou Y Q, Li C S, Xu L X 2002 J. Electron. Inf. Tech. 24 1932 (in Chinese) [燕英, 周荫清, 李春升, 许丽香 2002 电子与信息学报 24 1932]

    [6]

    Yu G M, Deng H T, Zhang C Y, Wu S J 2006 J. Syst. Eng. Electron. 28 997 (in Chinese) [俞根苗, 邓海涛, 张长耀, 吴顺君 2006 系统工程与电子技术 28 997]

    [7]

    Fang L L, Wang Y F 2008 J. Electron. Inf. Tech. 30 1316 (in Chinese) [房丽丽, 王岩飞 2008 电子与信息学报 30 1316]

    [8]

    Zhou P, Xiong T, Zhou S, Li Y C, Xing M D 2011 J. Electron. Inf. Tech. 33 622 (in Chinese) [周鹏, 熊涛, 周松, 李亚超, 邢孟道 2011 电子与信息学报 33 622]

    [9]

    Zhou S, Bao M, Zhou P, Xing M D, Bao Z 2011 J. Electron. Inf. Tech. 33 1420 (in Chinese) [周松, 包敏, 周鹏, 邢孟道, 保铮 2011 电子与信息学报 33 1420]

    [10]

    Almeida L B 1994 IEEE Trans. Signal Proc. 42 3084

    [11]

    Ozaktas H M, O Arikan, Kutay M A, Bozdagt G 1996 IEEE Trans. Signal Proc. 44 2141

    [12]

    Shinde S, Gadre V 2001 IEEE Trans. Signal Proc. 49 2545

    [13]

    Amein A S, Soraghan J J 2005 IEEE Trans. Signal Proc Let. 12 705

    [14]

    Amein A S, Soraghan J J 2007 IEEE Trans. Signal Proc. 55 4162

    [15]

    Clemente C, Soraghan J J 2012 IET Signal Processing. 6 503

    [16]

    Deng B, Li X, Wang H Q, Qin Y L, Wang J T 2011 IEEE Geosci. Remote S. 8 44

    [17]

    Chen S, Zhao H C, Zhang S N Chen Y 2013 Acta Phys. Sin. 62 218405 (in Chinese) [陈思, 赵惠昌, 张淑宁, 陈勇 2013 物理学报 62 218405]

    [18]

    Tao R, Deng B, Wang Y 2009 Fractional Fourier Transform (Beijing: Tsinghua University Press) p25 (in Chinese) [陶然, 邓兵, 王越, 2009 分数阶傅里叶变换及其应用(北京:清华大学出版社)第25 页]

    [19]

    Capus C, Brown K 2003 J. Acoust. Soc. Am. 113 3253

计量
  • 文章访问数:  2359
  • PDF下载量:  598
  • 被引次数: 0
出版历程
  • 收稿日期:  2014-01-07
  • 修回日期:  2014-02-24
  • 刊出日期:  2014-06-05

基于分数阶傅里叶变换的弹载SAR成像算法

  • 1. 南京理工大学电子工程与光电技术学院, 南京 210094;
  • 2. 淮阴师范学院物理与电子电气工程学院, 淮安 223300
    基金项目: 

    国家自然科学基金(批准号:61301216)和江苏省普通高校研究生科研创新计划(批准号:CXZZ130206)资助的课题.

摘要: 针对弹载合成孔径雷达(SAR)回波信号的多普勒参数随斜距变化大及传统脉冲压缩成像算法分辨率低的问题,本文提出了一种基于分数阶傅里叶变换(FrFT)的弹载SAR成像算法. 首先建立弹载SAR末制导阶段回波信号模型,然后通过局部最优处理来测量回波信号的调频率,并以此计算FrFT的最优阶次,在最优阶次下分别对回波信号进行距离向和方位向的FrFT,从而得到成像区域的SAR图像,最后分别采用传统脉冲压缩成像算法与本文基于FrFT的成像算法进行仿真和实测对比实验. 实验结果表明,该算法能够对目标区域精确成像;由于在成像处理过程中,对每个距离向和方位向的回波信号进行独立的局部最优处理,因此该算法更适应于弹载SAR的非线性飞行轨迹,大大提高了弹载SAR的成像性能. 该研究成果在目标探测与识别,精确制导等领域中具有重要的应用价值.

English Abstract

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