Subspace-Based STAP in Airborne FDA Radar for Homogeneous Clutter Under Range Ambiguity

This article investigates subspace-based space–time adaptive processing (STAP) in airborne frequency diversity array (FDA) radar systems for homogeneous clutter under range ambiguity. The key point of subspace-based FDA-STAP is to accurately estimate the clutter rank and the clutter subspace. To tackle this issue, a subspace transformation matrix is constructed in the transmit–time–receive domain according to the element spacing ratio of transmit and receive arrays, the number of Doppler ambiguities, and the number of range ambiguities, which can model the radar scene accurately. Based on the proposed subspace transformation matrix, the clutter rank is accurately derived for all element spacing ratios, the number of Doppler ambiguities, and the number of range ambiguities, and then, the clutter subspace is reliably estimated. With the estimated clutter subspace, a subspace-based FDA-STAP method is provided. Furthermore, the maximum resolvable number of range ambiguities is derived. Numerical results verify that the derived clutter rank and the maximum resolvable number of range ambiguity are accurate, and the proposed FDA-STAP method has great performance advantages over related methods.