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宁江波, 李宇, 吴永胜, 迟骋, 李子高, 李淑秋. 一种频域−波数域峰值筛选的无源声呐宽带检测方法[J]. 声学学报, 2023, 48(3): 459-470. DOI: 10.15949/j.cnki.0371-0025.2023.03.007
引用本文: 宁江波, 李宇, 吴永胜, 迟骋, 李子高, 李淑秋. 一种频域−波数域峰值筛选的无源声呐宽带检测方法[J]. 声学学报, 2023, 48(3): 459-470. DOI: 10.15949/j.cnki.0371-0025.2023.03.007
NING Jiangbo, LI Yu, WU Yongsheng, CHI Cheng, LI Zigao, LI Shuqiu. A method for passive sonar broadband target detection based on peak filtering in frequency-wavenumber domain[J]. ACTA ACUSTICA, 2023, 48(3): 459-470. DOI: 10.15949/j.cnki.0371-0025.2023.03.007
Citation: NING Jiangbo, LI Yu, WU Yongsheng, CHI Cheng, LI Zigao, LI Shuqiu. A method for passive sonar broadband target detection based on peak filtering in frequency-wavenumber domain[J]. ACTA ACUSTICA, 2023, 48(3): 459-470. DOI: 10.15949/j.cnki.0371-0025.2023.03.007

一种频域−波数域峰值筛选的无源声呐宽带检测方法

A method for passive sonar broadband target detection based on peak filtering in frequency-wavenumber domain

  • 摘要: 在水声信号处理中, 传统的无源声呐宽带目标检测在多目标、强干扰的复杂环境中输出信噪比低, 使得检测性能急剧下降。针对此问题, 提出一种基于均匀线列阵在频域−波数域上宽带信号能量分布特性进行目标检测的方法。该方法首先将阵列信号转换到频域−波数域, 利用不同频率下波数主瓣、旁瓣宽度特征以及空间分布特征, 设计针对主瓣的判别与分配方法, 实现对同一目标不同频率下波数谱主瓣判别, 使用主瓣能量累积、主瓣数目累积的方式来形成方位谱, 从而进行目标检测。理论分析和仿真结果表明, 所提方法只利用对目标检测有突出贡献的波数主瓣, 降低了旁瓣的影响, 有效提高了无源宽带水声目标的检测能力。海上试验数据处理结果表明, 目标输出信噪比相比子带峰值能量检测算法可提高5.58 dB, 较传统能量检测可提高8.73 dB, 计算时间相比传统能量检测降低46%, 验证了所提方法的有效性与实时性。

     

    Abstract: Traditional detection of broadband targets in passive sonars has low output signal-to-noise ratio and poor performance in a complex situation with multiple targets and strong interferences. To solve this problem, a target detection method is proposed based on the characteristics of the energy distribution of broadband signals in the frequency-wavenumber domain by using uniform linear array. The proposed method converts the array signal into the frequency-wavenumber domain and uses the characteristics of the width and the spatial distribution of the main lobes and the side lobes to discriminate the main lobes in the wavenumber domain. After discriminating the main lobes of the same target at different frequencies, the accumulation of main lobe energy and the number of main lobes are used as the azimuth spectra for target detection. The theoretical analysis and simulations show the proposed method only utilizes the main lobes which have prominent contributions to target detection, thereby reducing the influence of the side lobes dramatically and improving the detection performance significantly. The results of trial data processing show that the output signal-to-noise ratio of the proposed method can be increased by 5.58 dB compared to SPED and 8.73 dB compared to CED. In addition, the computing time is decreased by 46% compared to CED, which validates the superiority of the proposed method.

     

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