A self-calibration algorithm for cyclostationary signals and its uniqueness analysis

Abstract

A self-calibration DOA estimation algorithm for cyclostationary source signals is presented in which the effects of the sensor gain and phase shift uncertainty have been eliminated. The uniqueness conditions and the asymptotic consistency of the estimates are discussed. An alternating projecting optimization algorithm is provided which lessens the computational load involved in the nonlinear multivariate optimization problem. A numerical example is presented to show the effectiveness of the algorithm.