基于S变换的时频特征提取与目标识别
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摘要
目标的时间-频率联合分布能够很好地反映目标物理结构特征,可以作为雷达目标识别的一个有效手段。针对现有时频分析方法存在的识别率低和抗噪性能差等问题,提出一种基于S变换的空间目标回波信号电磁特征提取与识别方法。首先对目标的雷达回波进行时频分析,得出在较大方位角变化范围内和不同信噪比情况下,目标S变换的时频分布具有相对不变性的结论;然后基于这种稳定的时频分布特征,采用最小贴近度的方法进行分类识别。针对不同目标模型的仿真结果表明,该方法的识别率高于其他时频分析方法并且具有很好的鲁棒性。
The time-frequency joint distribution of a target reflects well its physical structural property so it can be used as an effective means of radar target recognition.Aiming at the problems of low identification rate and poor antinoise performance in existing time-frequency analysis methods,a method of radar target electromagnetic features extraction and recognition based on S-transform is proposed.The time-frequency distribution of a target is first analyzed by the S-transform and the stability of time-frequency distribution within a large angle range and signal-noise ratio is derived.Based on these stable signatures,a recognition algorithm is proposed.Finally,the identification of different target models are performed and the results demonstrate that the method provided in this article has higher recognition performance and better robustness than other time-frequency analysis methods.
The time-frequency joint distribution of a target reflects well its physical structural property so it can be used as an effective means of radar target recognition.Aiming at the problems of low identification rate and poor antinoise performance in existing time-frequency analysis methods,a method of radar target electromagnetic features extraction and recognition based on S-transform is proposed.The time-frequency distribution of a target is first analyzed by the S-transform and the stability of time-frequency distribution within a large angle range and signal-noise ratio is derived.Based on these stable signatures,a recognition algorithm is proposed.Finally,the identification of different target models are performed and the results demonstrate that the method provided in this article has higher recognition performance and better robustness than other time-frequency analysis methods.
引文
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[2]冯德军,陶华敏,丹梅,等.弹道目标雷达宽带识别仿真与评估[J].系统仿真学报,2006,18(1):225-228.Feng Dejun,Tao Huamin,Dan Mei,et al.Si mulation andassessment of ballistic target recognition using widebandradar[J].Jounal of System Si mulation,2006,18(1):225-229.(in Chinese)
[3]鲜明,庄钊文,郭桂蓉,等.基于时频分析的飞机目标识别[J].国防科技大学学报,1997,19(3):7-11.Xian Ming,Zhuang Zhaowen,Guo Guirong,et al.Tar-gets recognition based on ti me-frequency analysis[J].Journal of National University of Defense Technology,1997,19(3):7-11.(in Chinese)
[4]胡广书.现代信号处理教程[M].北京:清华大学出版社,2004:97-113.Hu Guangshu.Modern signal processing course[M].Beijing:Tsinghua University Press,2004:97-113.(inChinese)
[5]Stockwell R G,Mansinhal L,Lowe R P.Localization ofthe complex spectrum:the S-transform[J].IEEE Tran-sactions on Signal Processing,1996,44(4):998-1001.
[6]邹文.S变换时频分析技术及其在地震勘探中的应用研究[D].武汉:中国地质大学,2005:12-14.Zou Wen.S-transformti me-frequency analysis technologyand its application research in seismic processing[D].Wuhan:China University of Geosciences,2005:12-14.(in Chinese)
[7]辛欣,张效民.基于S变换的水中目标特征提取[J].电声技术,2007,31(1):10-12.Xin Xin,Zhang Xiaomin.Feature extraction of target un-derwater based on S-transform[J].Audio Engineer,2007,31(1):10-12.(in Chinese)
[8]Assous S,Humeau A,Tartas M,et al.S-transformap-plied to laser doppler flowmetry reactive hyperemia signal[J].IEEE Transactions on Biomedical Engineering,2006,53(6):1032-1037.
[9]Dash P K,Behera HS,Lee I W C.Ti me sequence datamining using ti me-frequency analysis and soft computingtechniques[J].Applied Soft Computing,2008,8(1):202-215.
[10]Schi mmel M,Gallart J.The inverse S-transformin filterswith ti me-frequency localization[J].IEEE Transactionson Signal Processing,2005,53(11):4417-4422.
[11]Chen V C,Li F,Ho S S,et al.Analysis of micro-Dopplersignatures[J].Radar,Sonar and Navigation,IEE Proceed-ings,2003,150(4):271-276.
[12]Dangwei W,Xinyi M,Yi S.Radar target identification us-ing a likelihood ratio test and matching pursuit technique[J].Radar,Sonar and Navigation,IEE Proceedings,2006,153(6):509-515.
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