基于提升Keystone变换的声呐宽带自适应波束形成方法
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摘要
针对Keystone变换在宽带阵列预处理方面的优势和常规Keystone变换存在的阵元数据缺失问题,该文将自回归模型与常规Keystone变换相结合,提出一种基于提升Keystone变换的声呐宽带自适应波束形成算法。该算法首先将常规Keystone变换应用于宽带阵列信号的相位对齐,接着采用自回归模型对变换后各频段缺失的阵元数据进行预测补偿,最后通过稳健自适应波束形成处理获得目标方位输出结果。仿真实验结果表明,基于提升Key-stone变换的宽带自适应波束形成算法性能优于常规Keystone自适应算法、指向最小方差自适应算法和聚焦自适应算法。
Keystone transform is an effective broadband array signal pre-processing method, but it has a main problem of array data missing. In order to solve this problem, an enhanced Keystone transform algorithm,which combines the autoregression model with traditional Keystone transform, is proposed in this paper for sonar broadband adaptive beamforming. After phase alignment of broadband array signal using traditional Keystone transform, autoregression models for each frequency are constructed to compensate the missing array data. Then, a robust adaptive beamforming approach is utilized to obtain the target bearing results. The results of simulation studies indicate that the proposed broadband adaptive beamforming algorithm based on enhanced Keystone transform outperforms the beamforming algorithms based on traditional Keystone transform, steered minimum variance and frequency focusing.
Keystone transform is an effective broadband array signal pre-processing method, but it has a main problem of array data missing. In order to solve this problem, an enhanced Keystone transform algorithm,which combines the autoregression model with traditional Keystone transform, is proposed in this paper for sonar broadband adaptive beamforming. After phase alignment of broadband array signal using traditional Keystone transform, autoregression models for each frequency are constructed to compensate the missing array data. Then, a robust adaptive beamforming approach is utilized to obtain the target bearing results. The results of simulation studies indicate that the proposed broadband adaptive beamforming algorithm based on enhanced Keystone transform outperforms the beamforming algorithms based on traditional Keystone transform, steered minimum variance and frequency focusing.
引文
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[11]张宁,汤小为,汤俊.基于Keystone变换预处理的宽带波束形成方法[J].清华大学学报(自然科学版),2013,53(7):991-994.doi:10.16511/j.cnki.qhdxxb.2013.07.017.ZHANG Ning,TANG Xiaowei,and TANG Jun.Broadband beamforming method based on Keystone transform preprocessing[J].Journal of Tsinghua University(Science andTechnology),2013,53(7):991-994.doi:10.16511/j.cnki.qhdxxb.2013.07.017.
[12]ZHAO Yongbo,WANG Juan,HUANG Lei,et al.Low complexity Keystone transform without interpolation for dim moving target detection[C].Proceedings of IEEE CIEInternational Conference on Radar,Chengdu,China,2011:1745-1748.doi:10.1109/CIE-Radar.2011.6159907.
[13]MARANDA B.Efficient digital beamforming in the frequency domain[J].Journal of the Acoustical Society of America,1989,86(5):1813-1819.doi:10.1121/1.398614.
[14]QIAN Yuning,YAN Ruqiang,and HU Shijie.Bearing degradation evaluation using recurrence quantification analysis and Kalman filter[J].IEEE Transactions on Instrumentation and Measurement,2014,63(11):2599-2610.doi:10.1109/TIM.2014.2313034.
[15]张玲华,郑宝玉.随机信号处理[M].北京:清华大学出版社,2008:97-101.ZHANG Linghua and ZHENG Baoyu.Stochastic Signal Processing[M].Beijing:Tsinghua University Press,2008:97-101.
[16]GOTO S,NAKAMURA M,and UOSAKI K.Online spectral estimation of nonstationary time-series based on AR model parameter-estimation and order selection with a forgetting factor[J].IEEE Transactions on Signal Processing,1995,43(6):1519-1522.doi:10.1109/78.388868.
[2]钱宇宁,曹欣荣,陈亚伟,等.被动声呐盲分离自适应-自适应波束形成算法研究[J].电子与信息学报,2017,39(10):2390-2396.doi:10.11999/JEIT170099.QIAN Yuning,CAO Xinrong,CHEN Yawei,et al.Research on adaptive-adaptive beamforming algorithm based on blind separation for passive sonar[J].Journal of Electronics&Information Technology,2017,39(10):2390-2396.doi:10 .11999/JEIT170099.
[3]YAN Chao,ZHANG Weiyu,XU Peng,et al.An improved robust adaptive beamforming based on worst-case performance optimization[J].The Journal of the Acoustical Society of America,2017,142(4):2729-2731.doi:10.1121/1.5014963.
[4]LIU Wei and LANGLEY R J.An adaptive wideband beamforming structure with combined subband decomposition[J].IEEE Transactions on Antennas and Propagation,2009,57(7):2204-2207.doi:10.1109/TAP.2009.2021978.
[5]BUCRIS Y,COHEN I,and DORON M A.Bayesian focusing for coherent wideband beamforming[J].IEEETransactions on Audio,Speech,and Language Processing,2012,20(4):1282-1296.doi:10.1109/TASL.2011.2175384.
[6]SOMASUNDARAM S D.Wideband robust capon beamforming for passive sonar[J].IEEE Journal of Oceanic Engineering,2013,38(2):308-322.doi:10.1109/JOE.2012.2223560.
[7]LI Dong,ZHAN Muyang,LIU Hongqing,et al.A robust translational motion compensation method for ISARimaging based on keystone transform and fractional fourier transform under low SNR environment[J].IEEETransactions on Aerospace and Electronic Systems,2017,53(5):2140-2156.doi:10.1109/TAES.2017.2683599.
[8]HUANG Penghui,XIA Xianggen,LIAO Guisheng,et al.Ground moving target imaging based on Keystone transform and coherently integrated CPF with a singlechannel SAR[J].IEEE Journal of Selected Topics in Applied Earth Observation and Remote Sensing,2017,10(12):5686-5694.doi:10.1109/JSTARS.2017.2742580.
[9]章建成,苏涛,吕倩.基于运动参数非搜索高速机动目标检测[J].电子与信息学报,2016,38(6):1460-1467.doi:10.11999/JEIT151042.ZHANG Jiancheng,SU Tao,and LüQian.High-speed maneuvering target detection based on non-searching estimation of motion parameters[J].Journal of Electronics&Information Technology,2016,38(6):1460-1467.doi:10.11999/JEIT151042.
[10]SUN Zhi,LI Xiaolong,YI Wei,et al.Detection of weak maneuvering target based on Keystone transform and matched filtering process[J].Signal Processing,2017,140:127-138.doi:10.1016/j.sigpro.2017.05.013.
[11]张宁,汤小为,汤俊.基于Keystone变换预处理的宽带波束形成方法[J].清华大学学报(自然科学版),2013,53(7):991-994.doi:10.16511/j.cnki.qhdxxb.2013.07.017.ZHANG Ning,TANG Xiaowei,and TANG Jun.Broadband beamforming method based on Keystone transform preprocessing[J].Journal of Tsinghua University(Science andTechnology),2013,53(7):991-994.doi:10.16511/j.cnki.qhdxxb.2013.07.017.
[12]ZHAO Yongbo,WANG Juan,HUANG Lei,et al.Low complexity Keystone transform without interpolation for dim moving target detection[C].Proceedings of IEEE CIEInternational Conference on Radar,Chengdu,China,2011:1745-1748.doi:10.1109/CIE-Radar.2011.6159907.
[13]MARANDA B.Efficient digital beamforming in the frequency domain[J].Journal of the Acoustical Society of America,1989,86(5):1813-1819.doi:10.1121/1.398614.
[14]QIAN Yuning,YAN Ruqiang,and HU Shijie.Bearing degradation evaluation using recurrence quantification analysis and Kalman filter[J].IEEE Transactions on Instrumentation and Measurement,2014,63(11):2599-2610.doi:10.1109/TIM.2014.2313034.
[15]张玲华,郑宝玉.随机信号处理[M].北京:清华大学出版社,2008:97-101.ZHANG Linghua and ZHENG Baoyu.Stochastic Signal Processing[M].Beijing:Tsinghua University Press,2008:97-101.
[16]GOTO S,NAKAMURA M,and UOSAKI K.Online spectral estimation of nonstationary time-series based on AR model parameter-estimation and order selection with a forgetting factor[J].IEEE Transactions on Signal Processing,1995,43(6):1519-1522.doi:10.1109/78.388868.