短驻留和低重频条件下的飞机目标识别方法研究
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摘要
针对现代相控阵雷达通常难以满足足够长的波束驻留时间和足够高的脉冲重复频率,从而导致目标识别性能下降的问题,以直升机为例建立了飞机目标旋转桨叶回波的数学模型,并深入分析了波束驻留时间和脉冲重复频率对调制特征的影响;在此基础上,提出一种基于奇异谱分析的飞机目标识别方法.该方法利用三类飞机目标调制谱线数目存在数量级上的差别,通过估算奇异谱中大特征值的个数来估算旋转桨叶回波信号中的谐波个数,进而实现三类飞机目标的识别.仿真结果表明,该方法平均识别率优于95%,从而验证了本文所提方法的有效性.
It is usually difficult for modern phased array radar to satisfy long enough accumulation time and high enough pulse repetition frequency, which results in the performance degradation of target recognition. In view of this problem, this paper takes helicopter as an example to establish a mathematical model of rotating blade echo, and deeply analyses the influence of accumulation time and pulse repetition frequency on modulation characteristics. On this basis, the paper proposes a method of airplane target recognition based on singular spectrum analysis. The proposed method makes use of the order of magnitude difference in the number of target modulation spectral lines for three types of aircraft, and by estimating the number of large eigenvalue in the singular spectrum,to estimate the number of harmonics in the rotating blade echo signal, and further to realize identification on three kinds of aircraft targets. The simulation results show that the method achieves an average recognition rate of more than 95%, thus verifying the effectiveness of the proposed method.
It is usually difficult for modern phased array radar to satisfy long enough accumulation time and high enough pulse repetition frequency, which results in the performance degradation of target recognition. In view of this problem, this paper takes helicopter as an example to establish a mathematical model of rotating blade echo, and deeply analyses the influence of accumulation time and pulse repetition frequency on modulation characteristics. On this basis, the paper proposes a method of airplane target recognition based on singular spectrum analysis. The proposed method makes use of the order of magnitude difference in the number of target modulation spectral lines for three types of aircraft, and by estimating the number of large eigenvalue in the singular spectrum,to estimate the number of harmonics in the rotating blade echo signal, and further to realize identification on three kinds of aircraft targets. The simulation results show that the method achieves an average recognition rate of more than 95%, thus verifying the effectiveness of the proposed method.
引文
[1]张群,罗迎.雷达目标微多普勒效应[M].北京:国防工业出版社,2013:1-10.
[2]SETLUR P,AHMAD F,AMIN M.Helicopter radar return analysis:estimation and blade number selection[J].Signal Processing,2011,91:1409-1424.
[3]ZUO Lei,LI Ming,ZHANG Xiaowei,et al.Two helicopter classification methods with a high pulse repetition frequency radar[J].IET Radar,Sonar and Navigation,2013,7(3):312-320.
[4]杨予昊,李士国.基于功率谱AMSF的微动特征提取算法[J].空军预警学院学报,2013,27(3):190-194.
[5]夏鹏,万显荣,易建新.外辐射源雷达目标旋转部件微动参数估计[J].电波科学学报,2016,31(4):676-682.
[6]CHEN V C.雷达中的微多普勒效应[M].吴顺君,杜兰,刘宏伟,译.北京:电子工业出版社,2013:92-96.
[7]HASSANI H.Singular spectrum analysis:methodology and comparison[J].Journal of Data Science,2007,5:239-257.
[8]de WIT J J M,HARMANNY R I A,MOLCHANOV P.Radar micro-Doppler feature extraction using the singular value decomposition[C]//Proceedings of 2014 International Radar Conference.Lille,France,2014:1-6.
[9]姜悦.基于微多普勒的飞机目标时频域特征提取[D].西安:西安电子科技大学,2014:16-18.
[2]SETLUR P,AHMAD F,AMIN M.Helicopter radar return analysis:estimation and blade number selection[J].Signal Processing,2011,91:1409-1424.
[3]ZUO Lei,LI Ming,ZHANG Xiaowei,et al.Two helicopter classification methods with a high pulse repetition frequency radar[J].IET Radar,Sonar and Navigation,2013,7(3):312-320.
[4]杨予昊,李士国.基于功率谱AMSF的微动特征提取算法[J].空军预警学院学报,2013,27(3):190-194.
[5]夏鹏,万显荣,易建新.外辐射源雷达目标旋转部件微动参数估计[J].电波科学学报,2016,31(4):676-682.
[6]CHEN V C.雷达中的微多普勒效应[M].吴顺君,杜兰,刘宏伟,译.北京:电子工业出版社,2013:92-96.
[7]HASSANI H.Singular spectrum analysis:methodology and comparison[J].Journal of Data Science,2007,5:239-257.
[8]de WIT J J M,HARMANNY R I A,MOLCHANOV P.Radar micro-Doppler feature extraction using the singular value decomposition[C]//Proceedings of 2014 International Radar Conference.Lille,France,2014:1-6.
[9]姜悦.基于微多普勒的飞机目标时频域特征提取[D].西安:西安电子科技大学,2014:16-18.