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功率谱密度消频散变换被动估计脉冲声源距离

刘建设 朱广平 殷敬伟 陈文剑 孙辉

刘建设, 朱广平, 殷敬伟, 陈文剑, 孙辉. 功率谱密度消频散变换被动估计脉冲声源距离[J]. 电子与信息学报, 2024, 46(9): 3592-3601. doi: 10.11999/JEIT231408
引用本文: 刘建设, 朱广平, 殷敬伟, 陈文剑, 孙辉. 功率谱密度消频散变换被动估计脉冲声源距离[J]. 电子与信息学报, 2024, 46(9): 3592-3601. doi: 10.11999/JEIT231408
LIU Jianshe, ZHU Guangping, YIN Jingwei, CHEN Wenjian, SUN Hui. Passive Pulse Source Ranging Using De-dispersion Transform of Power Spectral Density[J]. Journal of Electronics & Information Technology, 2024, 46(9): 3592-3601. doi: 10.11999/JEIT231408
Citation: LIU Jianshe, ZHU Guangping, YIN Jingwei, CHEN Wenjian, SUN Hui. Passive Pulse Source Ranging Using De-dispersion Transform of Power Spectral Density[J]. Journal of Electronics & Information Technology, 2024, 46(9): 3592-3601. doi: 10.11999/JEIT231408

功率谱密度消频散变换被动估计脉冲声源距离

doi: 10.11999/JEIT231408
基金项目: 国家重点研发计划项目 (2021YFC2801200)
详细信息
    作者简介:

    刘建设:男,博士生,研究方向为水声信号处理

    朱广平:男,副教授,研究方向为水声目标探测

    殷敬伟:男,教 授,研究方向为水声通信

    陈文剑:男,副教授,研究方向为水声目标散射

    孙辉:男,教 授,研究方向为水声物理

    通讯作者:

    朱广平 guangpingzhu@hrbeu.edu.cn

  • 中图分类号: TN929.3

Passive Pulse Source Ranging Using De-dispersion Transform of Power Spectral Density

Funds: The National Key Research and Development Program of China (2021YFC2801200)
  • 摘要: 浅海中传播的低频声波具有多模态特征和频散效应。对接收声信号消频散变换(DDT)可以消除频散效应,实现被动估计声源距离。针对消频散变换存在的测距多值问题,该文提出一种利用功率谱密度消频散变换的被动测距方法(PSD-DDT)。首先使用声场模型KRAKEN计算模态的水平波数;其次在只知道波导不变量大概范围的情况下,估计两个模态之间的频散常数;然后对保留了模态间干涉项的功率谱密度进行消频散变换;最后获得目标距离的估计值为PSD-DDT极大值对应的自变量与频散常数的比值。另外,当海洋参数未知时,需要分别对待测声源和引导声源进行PSD-DDT,利用自变量的比值确定声源距离,这种方法不需要估计频散常数。通过仿真和海试验证了PSD-DDT方法被动测距的有效性,并分析了波导不变量、模态阶数、噪声等因素对距离估计结果的影响。基于黄海试验结果,与DDT方法相比,PSD-DDT的测距误差下降了约49.2%。在35 km范围内最优波导不变量对应的平均相对误差约2.55%,被动测距精度较高。
  • 图  1  信号仿真

    图  2  20 km信号的DDT结果

    图  3  模态频散常数估计

    图  4  PSD-DDT结果

    图  5  海上试验概况

    图  6  引导声源

    图  7  引导声源的PSD-DDT结果

    图  8  测距结果对比

    表  1  仿真参数

    深度(m)声速(m/s)密度(g/cm3)衰减(dB/λ)
    海水6015001.00
    海底17001.80.2
    下载: 导出CSV

    表  2  波导常数估计结果

    m-n阶数 $ \beta $ $ {\gamma _{{mn}}} $ 拟合指标R2
    1-2 1.136 2.273 0.9997
    2-3 1.085 5.186 0.9999
    1-2 1.111 2.616 0.9985
    2-3 4.478 0.9998
    1-2 1.200 1.646 0.9444
    2-3 2.816 0.9254
    下载: 导出CSV

    表  3  PSD-DDT测距结果: $ \beta $=1.111

    真实距离(km)r12(km)误差(%)r23(km)误差(%)测距均值平均误差(%)
    2019.492.5320.321.6219.910.46
    4038.992.5340.641.6239.820.46
    6059.241.2660.741.2559.990.01
    8079.880.1480.851.0680.370.46
    10099.760.24101.841.84100.800.80
    下载: 导出CSV

    表  4  PSD-DDT测距结果: $ \beta $=1.200

    真实距离(km)r12(km)误差(%)r23(km)误差(%)测距均值平均误差(%)
    2020.663.2921.668.3221.165.80
    4041.924.8143.338.3242.626.56
    6062.584.3164.637.7263.616.01
    8083.854.8185.947.4384.906.12
    100105.125.12106.896.89106.016.01
    下载: 导出CSV

    表  5  测距方法评价

    测距方法MAE(km)RMSE(km)MRE(%)
    DDT($ \beta $= 1)3.224.3612.03
    PSD-DDT($ \beta $= 1)1.522.106.11
    PSD-DDT($ \beta $= 1.2)0.711.332.55
    下载: 导出CSV
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出版历程
  • 收稿日期:  2023-12-22
  • 修回日期:  2024-07-04
  • 网络出版日期:  2024-08-02
  • 刊出日期:  2024-09-26

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