A High-Resolution Eigenspace Direction-of-Arrival Estimation Method with an Unknown Number of Sources
Chen Qian, Xinkai Hao, Yue Wang, Yi Yang, Xiaoyuan Li · Journal of Marine Science and Engineering · 2026
The Eigenspace method has been widely applied in the ultrasonic field, and this method can improve the resolution and achieve good robustness. However, all existing methods require the number of sources in the space to be known. This paper proposes a high-resolution direction-of-arrival (DOA) estimation method based on the Eigenspace theory with an unknown number of sources in the PM domain. The proposed method first decomposes the received signals of a circular array into orthogonal PM signals and then extends the Eigenspace method into the phase mode (PM) domain. Since the existing Eigenspace methods project the optimal beam scanning vector onto the signal subspace, the number of sources needs to be known in advance. However, in practical scenarios, the number of sources is unknown. The proposed method employs the combination term of the PM covariance matrix and its eigenvalues to perform power operations, which can approximately achieve the closed-form expressions of the relevant parameters for the signal subspace and the noise subspace. Finally, high-resolution DOA estimation is achieved under the condition of an unknown number of sources. Simulation and experimental results demonstrate the effectiveness of the proposed method in high-resolution DOA with an unknown number of sources.