一种波束谱特征加权的水下弱目标检测方法

A Method for Undersea Weak Target Detection Based on Beam-spectrum Feature Weighting

  • 摘要: 实际水下被动信号处理中,感兴趣的弱目标往往只在所处理频段的某些频率分量上表现出相对明显的谱特征,现有基于能量累加的后置处理方式存在谱能量小于噪声的目标被平滑的问题,最终导致目标无法被有效检测。针对该问题,本文提出一种新的自适应波束形成后置处理方法,通过Eckart最优滤波器从波束信号谱中提取感兴趣的频谱,从而求取波束谱加权值,从而实现弱目标信号的增强。所提方法通过实际拖曳阵和舷侧阵的数据来验证,从实验结果来看,该方法在浅海多干扰环境下,对弱目标能够获得3 dB左右的弱目标检测增益。

     

    Abstract: In pracital underwater passive signal processing, weak target be interested in only in certain frequency component spectrum processing shows relatively obvious spectral characteristics, the existing post-processing method based on energy accumulation exist spectrum energy is less than the noise of the target is a smooth, eventually led to be the target cannot be effective detection. In order to solve this problem, a new adaptive beamforming post-processing method is proposed in this paper, in which the spectrum of interest is extracted from the beam signal spectrum by Eckart optimal filter, and the weighted value of the beam spectrum is obtained. Thus, the weak target signal can be enhanced. The proposed method is verified by the actual towed array and the flank array data. According to the experimental results, the proposed method can obtain a weak target detection gain of about 3 dB for weak targets in the shallow sea multi-interference environment.

     

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