Abstract:

Passive radar usually encounters aggravated multipath interferences, which nonetheless provide effective signal sources for array calibration. A novel approach for array calibration in passive radar is proposed, exploiting the strongest multipath signal and array rotation. Firstly, the time-domain correlation between the surveillance and reference signals is employed to extract the strongest multipath signal. And then,the array rotation which provides both additional calibration sources and priori knowledge about the rotating angle is utilized. Following that, the estimation of the array amplitude mismatch by comparison on amplitudes, the direction of arrival (DOA) of the strongest multipath signal and the array phase mismatch are finally estimated using the incorporation of maximum likelihood (ML) and least square (LS) algorithms. The applicable condition of the proposed approach is investigated, and the Cramer-Rao lower bound (CRLB) for DOA of the strongest -multipath-signal and the array phase mismatch is also derived. Numerical simulation and field data results demonstrate the behavior and effectiveness of the proposed algorithm.