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基于空间变换预处理的噪声子空间投影法

陆典

陆典. 基于空间变换预处理的噪声子空间投影法[J]. 电子与信息学报, 2023, 45(12): 4382-4390. doi: 10.11999/JEIT230553
引用本文: 陆典. 基于空间变换预处理的噪声子空间投影法[J]. 电子与信息学报, 2023, 45(12): 4382-4390. doi: 10.11999/JEIT230553
LU Dian. A Noise Subspace Projection Method Based on Spatial Transformation Preprocessing[J]. Journal of Electronics & Information Technology, 2023, 45(12): 4382-4390. doi: 10.11999/JEIT230553
Citation: LU Dian. A Noise Subspace Projection Method Based on Spatial Transformation Preprocessing[J]. Journal of Electronics & Information Technology, 2023, 45(12): 4382-4390. doi: 10.11999/JEIT230553

基于空间变换预处理的噪声子空间投影法

doi: 10.11999/JEIT230553
详细信息
    作者简介:

    陆典:男,博士生,研究方向为阵列信号处理、水下目标探测等

    通讯作者:

    陆典 ludian@hrbeu.edu.cn

  • 中图分类号: TN919

A Noise Subspace Projection Method Based on Spatial Transformation Preprocessing

  • 摘要: 针对基于噪声子空间投影的空间谱合成技术对输入信噪比(SNR)要求较高的问题,该文提出一种基于空间变换预处理的改进噪声子空间投影法。在子阵维度上,对阵列数据进行拆分处理,得到空间-空间-频率3维数据;利用空间投影变换,将其重新投影为空间-频率2维数据,实现子阵维度相干累积,提高空间变换后输入信噪比;采用噪声子空间投影法,对变换后数据进行处理,实现空间谱合成。数值仿真和实测数据处理结果表明:相比噪声子空间投影法,在保持方位分辨率不变的前提下,所提方法对输入信噪比的最低要求降低约6 dB,有效提升了噪声子空间投影法的弱信源检测性能。
  • 图  1  ${\boldsymbol{X}}\left( {{w_l}} \right)$拆分示意图

    图  2  空间投影变换处理示意图

    图  3  2种方法输出空间谱(单信源)

    图  4  2种方法输出空间谱(等强度双信源)

    图  5  2种方法输出空间谱(不等强度双信源)

    图  6  2种方法正确检测信源概率

    图  7  2种方法方位估计均方根误差

    图  8  噪声子空间投影法对应时间方位历程图(a)

    图  9  所提方法对应时间方位历程图(a)

    图  10  噪声子空间投影法对应时间方位历程图(b)

    图  11  所提方法对应时间方位历程图(b)

    图  12  噪声子空间投影法对应时间方位历程图(c)

    图  13  所提方法对应时间方位历程图(c)

    图  14  噪声子空间投影法对应时间方位历程图

    图  15  所提方法对应时间方位历程图

    图  16  2种方法输出空间谱(t=200 s)

    表  1  数值仿真参数设置

    参数类型参数设置
    阵型水平线列阵
    阵元数量M32
    阵元间距$ d $2 m
    采样频率$ {f_s} $5 kHz
    正横方位
    信源方位$ {\theta _0} $
    中心频率$ {f_0} $375 Hz
    下载: 导出CSV

    表  2  2种方法对应空间谱对比度评价

    方法边缘锐度背景级(dB)
    噪声子空间投影法0.69–21.56
    所提方法0.98–48.67
    下载: 导出CSV

    表  3  数据处理参数设置

    参数类型参数设置
    阵型水平线列阵
    阵元数量M64
    阵元间距 $ d $4 m
    采样频率${f_{\rm{s}}}$5 kHz
    正横方位$ \theta $
    未知信源方位$ {\theta _0} $$ - 70^\circ , - 50^\circ , - 30^\circ , - 10^\circ ,10^\circ ,30^\circ ,50^\circ ,70^\circ $
    工作频段${f_{\rm{B}}}$100~180 Hz
    下载: 导出CSV
  • [1] WANG Zengkun, YANG Zhibo, WU Shuming, et al. An improved multiple signal classification for nonuniform sampling in blade tip timing[J]. IEEE Transactions on Instrumentation and Measurement, 2020, 69(10): 7941–7952. doi: 10.1109/TIM.2020.2980912
    [2] KIJANKA P, QIANG Bo, SONG Pengfei, et al. Robust phase velocity dispersion estimation of viscoelastic materials used for medical applications based on the multiple signal classification method[J]. IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, 2018, 65(3): 423–439. doi: 10.1109/TUFFC.2018.2792324
    [3] LI Jianfeng, ZHAO Gaofeng, LI Baobao, et al. A reduced dimension multiple signal classification–based direct location algorithm with dense arrays[J]. International Journal of Distributed Sensor Networks, To be published.
    [4] FENG Maoyuan, CUI Zhongma, YANG Yunxiu, et al. A reduced-dimension MUSIC algorithm for monostatic FDA-MIMO radar[J]. IEEE Communications Letters, 2021, 25(4): 1279–1282. doi: 10.1109/LCOMM.2020.3045440
    [5] SHENG Xueli, LU Dian, LI Yingsong, et al. Performance improvement of bistatic baseline detection[J]. IETE Journal of Research, To be published.
    [6] JIANG Xingbang, NI Gang, CAO Anjie, et al. Single-channel spatial spectrum estimation direction finding by the time-modulated linear array[J]. IEEE Antennas and Wireless Propagation Letters, 2021, 20(12): 2491–2495. doi: 10.1109/LAWP.2021.3115826
    [7] YANG Bin, LI Wenxing, LI Yuanyuan, et al. Robust adaptive null broadening beamforming based on subspace projection[J]. International Journal of Electronics, 2023, 110(1): 184–198. doi: 10.1080/00207217.2021.2024608
    [8] QI Bingbing and LIU Dunge. An enhanced spatial smoothing algorithm for coherent signals DOA estimation[J]. Engineering Computations, 2022, 39(2): 574–586. doi: 10.1108/EC-02-2021-0087
    [9] ZHENG Guimei, CHEN Chen, and SONG Yuwei. Real valued MUSIC method for height measurement of meter wave polarimetric MIMO radar based on matrix reconstruction[J]. Remote Sensing, 2022, 14(16): 4121. doi: 10.3390/rs14164121
    [10] WENG Liuqing, SONG Xiyu, LIU Zhenghong, et al. DOA estimation of indoor sound sources based on spherical harmonic domain beam-space MUSIC[J]. Symmetry, 2023, 15(1): 187. doi: 10.3390/sym15010187
    [11] LI Jie, CHEN Fangjiong, WANG Yide, et al. Spatial spectrum estimation of incoherently distributed sources based on low-rank matrix recovery[J]. IEEE Transactions on Vehicular Technology, 2020, 69(6): 6333–6347. doi: 10.1109/TVT.2020.2986783
    [12] 高杨, 李东生. 基于改良MUSIC和ALD-LCMV的自适应波束形成算法[J]. 探测与控制学报, 2015, 37(3): 24–29,39.

    GAO Yang and LI Dongsheng. Adaptive beamforming algorithm based on modified MUSIC and ADL-LCMV[J]. Journal of Detection &Control, 2015, 37(3): 24–29,39.
    [13] 王思秀, 郭文强, 汪晓洁, 等. 基于时空联合估计噪声子空间的MUSIC波束形成方法[J]. 计算机科学, 2021, 48(4): 282–287. doi: 10.11896/jsjkx.200300029

    WANG Sixiu, GUO Wenqiang, WANG Xiaojie, et al. MUSIC beam-forming method based on temporal and spatial union estimation of noise subspaces[J]. Computer Science, 2021, 48(4): 282–287. doi: 10.11896/jsjkx.200300029
    [14] 司伟建, 林晴晴. 利用延时预处理的DOA估计方法[J]. 哈尔滨工程大学学报, 2012, 33(7): 894–898. doi: 10.3969/j.issn.1006-7043.201108047

    SI Weijian and LIN Qingqing. A method of DOA estimation based on delay preprocessing[J]. Journal of Harbin Engineering University, 2012, 33(7): 894–898. doi: 10.3969/j.issn.1006-7043.201108047
    [15] 余华兵, 郑恩明, 陈新华. 基于相参累积预处理的空间谱估计方法[J]. 上海交通大学学报, 2020, 54(11): 1209–1217. doi: 10.16183/j.cnki.jsjtu.2019.332

    YU Huabing, ZHENG Enming, and CHEN Xinhua. A spatial spectrum estimation method based on coherent cumulative preprocessing[J]. Journal of Shanghai Jiao Tong University, 2020, 54(11): 1209–1217. doi: 10.16183/j.cnki.jsjtu.2019.332
    [16] 邱岚. 基于两次傅里叶变换的时域MUSIC波达方向估计[J]. 电讯技术, 2018, 58(10): 1206–1211.

    QIU Lan. Time-domain MUSIC for DOA estimation based on twice Fourier transform[J]. Telecommunication Engineering, 2018, 58(10): 1206–1211.
    [17] 李冰, 汪永明, 黄海宁. 基于时域解析估计的多重信号分类波束形成方法[J]. 上海交通大学学报, 2019, 53(8): 928–935. doi: 10.16183/j.cnki.jsjtu.2019.08.006

    LI Bing, WANG Yongming, and HUANG Haining. Multiple signal classification beam-forming method based on time domain analysis[J]. Journal of Shanghai Jiao Tong University, 2019, 53(8): 928–935. doi: 10.16183/j.cnki.jsjtu.2019.08.006
    [18] 武时龙. 基于分子阵预处理的最小方差无畸变响应波束形成方法[J]. 探测与控制学报, 2018, 40(6): 84–88.

    WU Shilong. Minimum variance undistorted response beam-forming algorithm based on sub-array preprocessing[J]. Journal of Detection &Control, 2018, 40(6): 84–88.
    [19] 余华兵, 郑恩明, 陈新华. 基于全相位预处理的时域多重信号分类波达方向估计方法[J]. 振动与冲击, 2020, 39(10): 242–248. doi: 10.13465/j.cnki.jvs.2020.10.033

    YU Huabing, ZHENG Enming, and CHEN Xinhua. The time-domain multiple signal classification DOA estimation method based on app-phase preprocessing[J]. Journal of Vibration and Shock, 2020, 39(10): 242–248. doi: 10.13465/j.cnki.jvs.2020.10.033
    [20] 郑恩明, 陈新华, 宋春楠. 基于全相位预处理的低旁瓣波束形成方法[J]. 兵工学报, 2018, 39(10): 1971–1978. doi: 10.3969/j.issn.1000-1093.2018.10.013

    ZHENG Enming, CHEN Xinhua, and SONG Chunnan. Low side-lobe beam-forming method based on all-phase preprocessing[J]. Acta Armamentarii, 2018, 39(10): 1971–1978. doi: 10.3969/j.issn.1000-1093.2018.10.013
    [21] 陈新华, 郑恩明. 基于分组时延预处理的时域波束形成方法[J]. 应用声学, 2019, 38(4): 545–552. doi: 10.11684/j.issn.1000-310X.2019.04.011

    CHEN Xinhua and ZHENG Enming. Time domain beam-forming algorithm based on sub-group & time delay preprocessing[J]. Journal of Applied Acoustics, 2019, 38(4): 545–552. doi: 10.11684/j.issn.1000-310X.2019.04.011
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出版历程
  • 收稿日期:  2023-06-06
  • 修回日期:  2023-08-10
  • 网络出版日期:  2023-08-17
  • 刊出日期:  2023-12-26

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