Joint 2-D angular and frequency estimation for uniform circular array

Investigates the problems of joint 2-D angular and frequency estimation based on uniform circular array (UCA). Based on the stacking of data matrix, real-processing of signal subspace, complex shift invariance equation and joint eigenvalue estimation, an algorithm is presented to solve this problem and handle the estimation jointly. It is shown that finally this problem turns to the estimation of the real joint eigenvalues of three real matrices and solve the joint eigenvalue estimation by a recently proposed simultaneous diagonalization algorithm. The advantages of the algorithm are attained, i.e. strong identifiability results and autopairing capacity. Theoretical analysis and simulation prove the effectivity of the algorithm.