An Enhanced Data-Driven Array Shape Estimation Method Using Passive Underwater Acoustic Data
An Enhanced Data-Driven Array Shape Estimation Method Using Passive Underwater Acoustic Data
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DOI：
10.3390/rs13091773
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发表时间：
2021-05
期刊：
影响因子：
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通讯作者：
Qisong Wu;Hao Zhang;Z. Lai;Youhai Xu;Shuai Yao;Jun Tao
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文献类型：
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作者：
Qisong Wu;Hao Zhang;Z. Lai;Youhai Xu;Shuai Yao;Jun Tao
在被动声纳阵列处理中，基于波束形成的信号增强技术往往由于被拖曳平台的快速战术机动、海流、水动力等因素造成的阵列失真而性能较差，本文提出了一种基于数据驱动的被动水声阵列形状估计公式。该方法首先利用基于假设理想阵列的波束赋形从机会源中检测出窄带分量，然后提取这些检测到的窄带分量的对应相位以获得时延差。然后，基于水听器阵列的时延差异缓慢变化和多个窄带分量的不同信干噪比的基本性质，提出了一种加权离群鲁棒卡尔曼平滑器来获得时延差的增强估计，并给出了其Cramer-Rao下界。最后，基于估计的时延差估计水听器阵列的形状。该公式充分利用了来自远距离水声目标的定向辐射噪声信号作为实时阵列形状估计的机会源，因此它不需要事先知道源的数目和方向。仿真和真实实验数据验证了该方法的有效性。
Beamforming-based signal enhancement technologies in passive sonar array processing often have poor performance due to array distortion caused by rapid tactical maneuvers of the towed platform, oceanic currents, hydrodynamic effects, etc. In this paper, an enhanced data-driven shape array estimation formulation is proposed using passive underwater acoustic data. Beamforming based on a hypothetically ideal array is firstly employed to perform the detection of narrow-band components from sources of opportunity, and the corresponding phases of these detected narrow-band components are subsequently extracted to acquire time-delay differences. Then, a weighted outlier-robust Kalman smoother is proposed to acquire enhanced estimates of the time-delay differences, since the underlying properties of slowly changing time-delay differences in the hydrophone array and diverse signal to interference and noise ratios in multiple narrow-band components are explored; and its Cramer–Rao Lower Bound is also provided. Finally, the hydrophone array shape is estimated based on the estimated time delay differences. The proposed formulation fully exploits directional radiated noise signals from distant underwater acoustic targets as sources of opportunity for real-time array shape estimation, and thus it requires neither the number nor direction of sources to be known in advance. The effectiveness of the proposed method is validated in simulations and real experimental data.