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基于线性回归的SAR目标方位角估计方法 被引量：5

A Method of Estimating Target Azimuth From SAR Image Based on Linear Regression
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摘要 方位角估计是合成孔径雷达(SAR)图像自动目标识别研究中的一个重要问题。一般而言,基于SAR图像的目标方位角估计方法应满足精度高、速度足够快、对目标部署条件的变化具有一定的稳健性。文中在分析现有的SAR图像目标方位角估计方法优缺点的基础上,给出了一种有效的基于线性回归的SAR图像目标方位角估计方法,并通过对大量实测MSTARSAR图像目标方位角的估计试验,详细分析了该方法对SAR图像目标方位角的估计性能。 Target azimuth estimation is very important for SAR ATR. Generally, any method of target azimuth estimation form SAR image should meet three requirements: First, it should be accurate. second, it should be fast. Finally, it also should be robust against target deployment variation. The advantages and disadvantages of current methods of target azimuth estimation from SAR image are analyzed in this paper. Then a method of estimating target azimuth from SAR image based on linear regression is proposed, and the performance of this estimation method is analyzed through a large number of experiments using real MSTAR SAR target image. [
作者 计科峰 匡纲要 郁文贤
机构地区 国防科技大学电子科学与工程学院
出处 《现代雷达》 CSCD 北大核心 2004年第11期26-29,共4页 Modern Radar
关键词 目标方位 SAR图像 估计方法 MSTAR 合成孔径雷达(SAR) 自动目标识别 稳健性 部署 细分 速度 synthetic aperture radar(SAR), image, azimuth estimation, automatic target recognition(ATR)
分类号 TN959.8.6 [电子电信—信号与信息处理]
  • 相关文献

参考文献13

  • 1Novak L M, Halversen S D, Owirka G J. Effects of polarization and resolution on SAR ATR. IEEE Transactions on Aerospace and Electronic Systems, 1997,33 (1): 102 ～ 115
  • 2Eric R Keydel. MSTAR extended operating conditions: A Tutorial. SPIE, 1996,2 757:228 ～ 242
  • 3Eric R Keydel. Signature prediction for model-based automatic target recognition. SPIE 1996,2 757:306 ～ 317
  • 4Wissinger J, Washburn R, Morgan D. Search algorithm for model-based SAR ATR SPIE, 1996,2 757:279 ～293
  • 5Joseph Diemunsch, John Wissinger. Moving and stationary target acquisition and recognition (MSTAR) model-based automatic target recognition: search technology for a robust ATR.SPIE, 1998, 3 370:481 ～492
  • 6Gil J Ettinger, Gregory A Klanderman, William M Wells. A probabolistic optimization approach to SAR feature matching.SPIE, 1996, 2 757:318 ～329
  • 7Liviu I Voicu, Ron Patton, Harley R Myler. Multi-criterion vehicle pose estimation for SAR ATR. SPIE, 1999, 3 721:497 ～506
  • 8Xu D X, Fisher Ⅲ J W, Principe J C. Pose estimation in SARusing an information theoretic criterion. Proc. of SPIE, 1998.218 ～229
  • 9Principe J, Zhao Q, Xu D. A novel ATR classifier exploiting pose information. In Proceedings of Image Understanding Workshop, 1998. 833 ～836
  • 10计科峰,匡纲要,郁文贤.SAR图像目标峰值提取及稳定性分析[J].现代雷达,2003,25(2):15-18. 被引量：12

二级参考文献8

  • 1[1]William Irving, Gil Ettinger. Classification of Target in Synthetic Aperture Radar Imagery via Quantized Grayscale Matching. 1999, SPIE Vol.3721: 320-331
  • 2[2]Air Force Research Laboratory, Model Based Vision Laboratory. Sensor Data Management System http://www.mbvlab.wpafb.af.mil/public/sdms/datasets/mstar/.
  • 3[3]William W Irving, Leslie M Novak, Alans S Willsky. A Multiresolution Approach to Discriminate in SAR Image. IEEE Transactions on Aerospace and Electronic Systems, 1997,33(4):1157～1168
  • 4[4]Munchurl Kim. Focus of Attention Based on Gamma Kernels for Automatic Target Recognition. doctor′s dissertation, University of FLORIDA, 1996
  • 5[5]L Noval etc., Effects of polarization and resolution on SAR ATR. IEEE Transactions on Aerospace and Electronic Systems, 1997,33(1):102～115
  • 6[6]Chris Oliver, Shaun Quegan. Understanding Synthetic Aperture Radar Images. Artech House, 1998
  • 7[7]Nipon Theera-Umpon etc.. Detection and Classification of MSTAR Objects Via Morphological Shared-Weight Nerual Networks. 1998, SPIE, Vol. 3370: 530～540
  • 8[8]E R Keydel ,S W Lee etc.. MSTAR Extended Operating Condition: A Tutorial. 1996, SPIE, Vol.2757:228～242

共引文献11

同被引文献63

  • 1陈利民,杨学志,张晰,郎海涛,孟俊敏.SAR舰船检测算法对比分析研究[J].遥感信息,2015,30(2):99-104. 被引量：9
  • 2Leslie M. Novak, Gregory J, Owirak, William W. Irving, Performance of 10- and 20- target MSE classifiers, IEEE Transactions on Aerospace and Electronic Systems VOL. 36, No. 4, Oct. 2000, p 1279-1289.
  • 3Eric R. Keydel, MSTAR Extended Operating Conditions:A Tutorial, SPIE Vol 2757,1996, p228-242.
  • 4Eric R. Keydel,Signature Prediction for Model-Based Automatic Target Recognition, SPIE Vol. 2757,1996. ,p306- 317.
  • 5Joseph Diemunsch, John Wissinger, Moving and Stationary Target Acquisition and Recognition ( MSTAR ) Model- Based Automatic Target Recognition: Search Technology for a Robust ATR,SPIE ,Vol. 3370,1998 ,p481-492.
  • 6William Irving, Gil Ettinger, Classification of Target in Synthetic Aperture Radar Imagery via Quantized Grayscale Matching, SPIE Vol. 3721,1999, p320-331.
  • 7Liviu I. Voicu, Ron Patton,Harley R. Myler,Multi-criterion vehicle pose estimation for SAR ATR, SPIE Vol. 3721, 1999, p497-506.
  • 8Xu,D. X. ,Fisher Ⅲ,J. W. ,and Principe,J. C. ,Pose estimation in SAR using an information theoretic criterion, Proc. of SPIE, 1998. , p218-229.
  • 9J. Principe, Q. Zhao and D. Xu. , A novel ATR classifier exploiting pose information. In Proceedings of Image Understanding Workshop ,833-836, Monterey, CA. , ( 1998 ).
  • 10Munchurl Kim, Focus of Attention Based on Gamma Kernels for Automatic Target Recognition, doctor' s dissertation, University of FLORIDA, 1996.

引证文献5

二级引证文献68

现代雷达
2004年 第11期

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