Background Coherent Noise Suppression in Fiber Optic Hydrophone Uniform Linear Arrays Using Covariance Matrix Reconstruction Based on Array Structure Priors

To suppress interference near the broadside of a uniform linear array (ULA) caused by background coherent noise in multiplexed fiber-optic hydrophone arrays, this paper proposes a covariance matrix reconstruction method based on array structure priors. The method exploits the difference between the block-diagonal covariance structure of coherent noise and the Hermitian Toeplitz structure of far-field target covariance matrices. Diagonal-block zeroing and diagonal averaging suppress coherent noise and restore target correlations, while matrix indefiniteness is retained to suppress residual interference and diagonal power compensation stabilizes the output. Simulations demonstrate effective interference suppression and target response preservation for both separated and coincident target and interference bearings. The method achieves a relatively high output signal to interference plus noise ratio (SINR) and maintains consistent performance under variations in input signal to noise ratio (SNR), number of snapshots, number of array elements and sensor position errors. Lake trial data in the 1–2 kHz band further demonstrate a 5.71 dB reduction in the average broadside interference peak relative to conventional beamforming, with only a 0.18 dB change in the average target-bearing peak and recovery of previously obscured potential weak target responses. The method requires neither prior knowledge of target bearings nor additional reference channels.