Sparse Direction of Arrival Estimation Method Based on Vector Signal Reconstruction with a Single Vector Sensor

TL;DR

This paper introduces a novel vector signal reconstruction method for single vector hydrophones, significantly enhancing DOA estimation accuracy and resolution in noisy, multi-source underwater environments.

Contribution

It proposes new sparse DOA estimation algorithms based on vector signal reconstruction, addressing limitations of traditional methods in complex, low SNR conditions.

Findings

Improved DOA estimation accuracy in multi-source scenarios

Enhanced resolution under low SNR conditions

Demonstrated effectiveness through simulations

Abstract

This study investigates the application of single vector hydrophones in underwater acoustic signal processing for Direction of Arrival (DOA) estimation. Addressing the limitations of traditional DOA estimation methods in multi-source environments and under noise interference, this research proposes a Vector Signal Reconstruction (VSR) technique. This technique transforms the covariance matrix of single vector hydrophone signals into a Toeplitz structure suitable for gridless sparse methods through complex calculations and vector signal reconstruction. Furthermore, two sparse DOA estimation algorithms based on vector signal reconstruction are introduced. Theoretical analysis and simulation experiments demonstrate that the proposed algorithms significantly improve the accuracy and resolution of DOA estimation in multi-source signals and low Signal-to-Noise Ratio (SNR) environments compared to traditional algorithms. The contribution of this study lies in providing an effective new method for DOA estimation with single vector hydrophones in complex environments, introducing new research directions and solutions in the field of vector hydrophone signal processing.