Abstract

To acquire the enhanced underwater ship-radiated noise signal in the presence of array shape distortion in a passive sonar system, the phase difference of the line-spectrum component in ship-radiated noise is often exploited to estimate the time-delay difference for the beamforming-based signal enhancement. However, the time-delay difference estimation performance drastically degrades with decreases of the signal-to-noise ratio (SNR) of the line-spectrum component. Meanwhile, although the time-delay difference estimation performance of the high-frequency line-spectrum components is generally superior to that of the low-frequency one, the phase difference measurements of the high-frequency line-spectrum component often easily encounter the issue of modulus 2π ambiguity. To address the above issues, a novel time-frequency joint time-delay difference estimation method is proposed in this paper. The proposed method establishes a data-driven hidden Markov model with robustness to phase difference ambiguity by fully exploiting the underlying property of slowly changing the time-delay difference over time. Thus, the phase difference measurements available for time-delay difference estimation are extended from that of low-frequency line-spectrum components in a single frame to that of all detected line-spectrum components in multiple frames. By jointly taking advantage of the phase difference measurements in both time and frequency dimensions, the proposed method can acquire enhanced time-delay difference estimates even in a low SNR case. Both simulation and at-sea experimental results have demonstrated the effectiveness of the proposed method.

Highlights

  • W represents the weighted least-square (WLS) estimation of time-delay difference at frame t, f, ηwhere ∆τm,t k,t m,k,t, and ∆ φm,k,t denote the estimate of frequency, signal-to-noise ratio (SNR), and phase difference for the kth linespectrum component at frame t, T stands for the number of frames, and K1 is the number of the detected low-frequency line-spectrum components, w is approximately given by respectively

  • We proposed a time-frequency joint time-delay difference estimation method for signal enhancement in the distorted towed hydrophone array

  • Since the phase difference measurements in both time and frequency dimensions are exploited jointly, the proposed method has the capability of acquiring enhanced time-delay difference estimates even in the low SNR case

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Summary

Introduction

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Time-delay difference estimation exploiting phase difference measurements of line-spectrum components of the underwater ship-radiated noise signal is still an open problem for beamforming-based signal enhancement in the presence of array shape distortion, in the low SNR case. A data-driven HMM with robustness to phase difference ambiguity is established to acquire enhanced time-delay difference estimates by taking advantage of the underlying property of slowly changing time-delay difference over time; The phase difference measurements available for time-delay difference estimation are extended from that of low-frequency line-spectrum components in a single frame to that of all detected line-spectrum components in multiple frames; The signal enhancement performance of the proposed method with a distorted array is close to that of the existing approach with a known array shape, even if the SNR of all the line-spectrum components is as low as 4 dB.

Signal Model
Time-Delay Difference Estimation Exploiting Phase Difference of Line-Spectrum
HMM for Time-Dealy Difference Estimation
Coarse Time-Delay Difference Estimation
Fine Time-Dealy Difference Estimation
Summary of the Signal Enhancement in the Distorted Towed Hydrophone Array
Calculation Complexity
Numerical Simulations and At-Sea Experiments
Simulation Results
Effectiveness Evaluation of the Proposed Method
Performance Comparison versus the SNR of the Line-Spectrum Component
Experimental Results of Real Sea Trial Data
Conclusions
Full Text
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