Joint 2-D Angle and Frequency Estimation for Uniform Circular Array

In this paper, we address the problem of joint 2-D angle and frequency estimation based on uniform circular array (UCA). We derive an ESPRIT-type algorithm to solve this problem and handle the estimation jointly by stacking the data matrix. We show that finally this problem turns to the estimation of the real joint eigenvalues of four real matrices. We solve the joint eigenvalue estimation by a recently proposed simultaneous diagonalization algorithm in order to achieve the advantages of the algorithm, i.e. strong identifiability results and autopairing capacity. The limitation of such strategy for UCA is also discussed