  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.
