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A new direction finding algorithm called conjugate propagator method （COP） for one-dimension signals was proposed. The new algorithm uses the array output and its conjugate form to extend the array aperture so that it can detect more signals than sensors and has better performance （in terms of resolution and angular precision） than OPM （or-thonormal-PM） and MUSIC algorithms. The mean square error （MSE） performance of COP was analyzed and the ana-lytical expression of MSE was given. The computational complexity of COP was analyzed also. Simulation results show the better performance of COP than OPM and MUSIC algorithms and the accordance between the theoretical results and the simulation results.

Abstract: This paper proposes a new computationally simple 2D direction finding algorithm for underwater acoustic coherent signals using a uniformly linear array of vector hydrophones. We decorrelate the source coherency by subarray averaging, and apply the propagator method to estimate automatically paired direction cosines embedded in the acoustical particle-velocity components of the vector hydrophone. Therefore, the presented algorithm requires neither the eigen-decomposition into signal/noise subspaces nor the 2D iteratively searching. In addition, because the vector-hydrophone array manifold contains no sensor location information, this new algorithm can offer high azimuth–elevation estimation accuracy by setting vector hydrophones to space much farther apart than a half-wavelength. The presented algorithm can be regarded as an improvement of SUMWE algorithm via replacing the pressure hydrophones there by vector hydrophones. Monte-Carlo simulations are presented to verify the efficacy of the proposed algorithm. [Copyright &y& Elsevier]

Abstract: This paper considers a new azimuth-elevation direction finding algorithm for multiple acoustic plane wave signals using acoustic vector array. Firstly, a planar-plus-an-isolated sensor array geometry [P. Li, J. Sun, B. Yu, Two-dimensional spatial spectrum estimation of coherent signals without spatial smoothing and eigendecomposition, IEE Proc.-Radar Sonar Navigat. 143(5) (October 1996) 295–299] is exploited and a cross-covariance matrix is defined. Then the propagator method is used to estimate the steering vectors of acoustic vector sensors. Finally, a closed-form, automatically paired azimuth-elevation angle estimates are derived. The presented algorithm shows high azimuth-elevation estimation accuracy due to array aperture extension. In addition, the new algorithm does not need the eigen-decomposition and 2D iterative searching, and is applicable to coherent (fully correlated) signals and spatially correlated noises. Therefore, the algorithm shows low computational complexity and robustness. Monte-Carlo simulations are presented to verify the effectiveness of the proposed algorithm. [Copyright &y& Elsevier]

Abstract: Recently, Wu et al. proposed a scheme for two-dimensional direction of arrival angle estimation for azimuth and elevation angles, using the propagator method. An advantage of this method over the classical subspace based algorithms, such as ESPRIT and MUSIC, is that it does not apply any eigenvalue decomposition (EVD) to the cross spectral matrix or singular value decomposition (SVD) to the received data. This significantly reduces the computational complexity, compared to the EVD and SVD. However, Wu''s method has some drawbacks, such as pair matching between the azimuth and elevation angle estimations for multiple different sources. Furthermore, Wu''s method has an estimation failure problem in the range of practical mobile elevation angles. The objectives of this paper are two-fold: (1) to overcome these two problems with less arithmetic operation counts than Wu used; and (2) to improve the performance significantly. To achieve these objectives, we propose an antenna array configuration which avoids these problems. Simulation results verify that the proposed scheme can remove these problems and give much better performance. [Copyright &y& Elsevier]