深海环境下利用噪声抵消器和经验模态分解的拖船干扰抑制方法

doi:10.12382/bgxb.2022.0732

摘要/Abstract

摘要：

针对深海环境下拖船自噪声在靠近端射和非端射方向产生的多途角扩展干扰影响拖曳声纳探测性能的问题,提出一种利用归一化最小均方误差(Normalized Least Mean Square,NLMS)噪声抵消器和经验模态分解(Empirical Mode Decomposition,EMD)的拖船干扰抑制方法。通过借鉴逆波束形成(Inverse Beamforming, IBF)的思想,对靠近端射方向的干扰波束进行相位补偿,重构出时域干扰信号,并将其作为自适应噪声抵消器的输入信号,基阵接收信号作为期望信号,利用NLMS方法调整滤波器的权值,进行初步干扰抑制。在此基础上通过EMD对噪声抵消器的输出结果进行分解得到多个本征模态(Intrinsic Mode Function, IMF)和残余分量,再利用匹配滤波方法筛选出用于重构拖船噪声的IMF,并在阵元域抵消完成干扰抑制,其中匹配模版为靠近端射方向频域干扰波束逆傅里叶变换得到的时域干扰信号。仿真数据和海试数据分析结果表明,与其他方法相比,所提方法能够大幅度抑制拖船自噪声产生的多途角扩展干扰,提升拖曳声纳在干扰盲区内对弱目标信号的检测能力。

关键词: 拖船噪声, 噪声抵消器, 经验模态分解, 检测能力, 干扰抑制

Abstract:

Aiming at the problem that the interference with multi-path and angle dispersion caused by the self-noise of tow ship in end-fire and non-end-fire directions affects the detection performance of towed sonar in deep-sea environment, a tow ship interference suppression method using,normalized least mean square (NLMS) and empirical mode decomposition (EMD) is proposed. Based on the idea of inverse beamforming, the time-domain interference signal is reconstructed by compensating the phase of interference beam near the end-fire direction, and it is taken as an input signal of adaptive noise canceller, the received signal of array is regarded as the desired signal, and NLMS algorithm is used to adjust the weight of filter for the primary interference suppression. On this basis, the output of the noise canceller is decomposed by EMD to get the intrinsic mode function and residual components, and the IMF used to reconstruct the tow ship noise is selected by the matched filtering method. And then the interference suppression is completed by meta-domain cancellation. The matching template is a time-domain interference signal obtained from the inverse Fourier transform of frequency-domain interference beam near the end-fire direction. The simulation data and sea trial data analysis show that, compared with other methods, the proposed method can be used ro suppress the interference with multi-path and angle dispersion caused by the self-noise of tow ship, and improve the towed sonar’s ability to detect the weak target signals in the interference blind area.

Key words: tow ship noise, noise canceller, empirical mode decomposition, detectability, interference suppression

中图分类号:

TB566

周健, 宋雪晶, 刘福臣, 张伟. 深海环境下利用噪声抵消器和经验模态分解的拖船干扰抑制方法[J]. 兵工学报, 2024, 45(2): 443-453.

ZHOU Jian, SONG Xuejing, LIU Fuchen, ZHANG Wei. Tow Ship Interference Suppression Method Using Noise Canceller and Empirical Mode Decomposition in Deep-sea Environment[J]. Acta Armamentarii, 2024, 45(2): 443-453.

图/表 14

图1 NLMS自适应噪声抵消器原理框图

Fig.1 Schematic diagram of NLMS adaptive noise canceller

图2 EMD方法流程图

Fig.2 Flowchart of EMD algorithm

图3 NLMS-EMD方法流程图

Fig.3 Flowchart of NLMS-EMD algorithm

图4 拖船噪声模拟

Fig.4 Tow ship noise simulation

图5 线列阵中心阵元接收到的本征声线

Fig.5 An eigenray received by the central element of a linear array

图6 不同方位目标信号CBF方法处理结果

Fig.6 CBF algorithm processing results of different azimuth target signals

图7 线列阵接收数据CBF方法处理

Fig.7 Data received by linear array for CBF algorithm processing

图8 EMD方法处理结果

Fig.8 Result of EMD algorithm

图9 不同收敛因子下的方法处理结果

Fig.9 Rocessing results of algorithms under the conditions of different convergence factors

图10 不同方法对线列阵模拟数据处理结果比较

Fig.10 Comparison of data processing results of linear array simulation by different algorithms

图11 不同方法处理得到的时间方位历程

Fig.11 The time and azimuth histories obtained by different algorithms

图12 海试数据不同时刻方法处理结果比较

Fig.12 Comparison of processing results of sea trial data at different times

图13 叠加目标信号后不同方法处理得到的时间方位历程图

Fig.13 The time and azimuth histories obtained by different algorithms afteroverlapping the target signals

图14 叠加目标信号后不同时刻方法处理结果比较

Fig.14 Comparison of processing results of algorithms at different time after overlapping the target signals

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