Algorithm for Joint Direction-of-Arrival and Frequency Estimation Based on Subspace Identification

In order to reduce the computational complexity and pair the parameters more easily, an algorithm for joint DOA and frequency estimation based on subspace identification is presented. Firstly, we construct a special state-space model and select an auxiliary matrix to restrain the noise. Secondly, we use subspace identification method to estimate the extended observable matrix, and get the estimation of system matrices using total least square (TLS) method. Finally, we get the estimation of DOA and frequency from the system matrices. The computational complexity of the algorithm is comparatively small, and the parameters estimated could be paired automatically. Simulation results are presented to demonstrate the effectiveness of the algorithm.