Tow Ship Interference Suppression Method Using Noise Canceller and Empirical Mode Decomposition in Deep-sea Environment

doi:10.12382/bgxb.2022.0732

Abstract

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

CLC Number:

TB566

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.

Figures/Tables 14

Fig.1 Schematic diagram of NLMS adaptive noise canceller

Fig.2 Flowchart of EMD algorithm

Fig.3 Flowchart of NLMS-EMD algorithm

Fig.4 Tow ship noise simulation

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

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

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

Fig.8 Result of EMD algorithm

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

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

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

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

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

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

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