Robust Adaptive Coherence Estimator Based on Ellipsoid Uncertainty Set Constraint

Adaptive Coherence Estimator (ACE) often suffers considerable performance degradation in the presence of steering vector errors. In this paper, a robust ACE detector based on the ellipsoid uncertainty set constraint is proposed. A detailed analysis of ACE detector is first conducted, which results in an interesting observation that scaling of the steering vector does not affect the statistical test of ACE. With this property exploited, a model for designing robust ACE detector is constructed and is subsequently converted into a convex optimization problem. Then, the solution to the problem is given with the powerful Newton-Raphson method. Simulation results show that the robustness of the proposed detector against the steering vector errors can be improved significantly compared with the standard ACE.