Reduced-Dimension FDA-STAP for Range-Ambiguous Clutter Rejection Under Limited Snapshots

Space-time adaptive processing (STAP) has been widely recognized as an effective technique for suppressing clutter in airborne radar systems. Nevertheless, range ambiguity can seriously affect the clutter rejection capability of conventional STAP methods. Frequency diverse array (FDA) radar provides additional degrees of freedom by exploiting frequency offsets across array elements, thereby offering an effective solution to the range ambiguity problem. Based on this advantage, FDA-STAP has been proposed and developed. However, when the available snapshots are insufficient, the performance of FDA-STAP may deteriorate significantly due to the high-dimensional adaptive processing requirement. To address this issue, this paper investigates reduced-dimension STAP for airborne FDA radar in range-ambiguous environments and proposes an enhanced reduced-dimension FDA-STAP method, referred to as ERD-FDA-STAP. First, the signal model of airborne FDA-STAP radar is established to describe the received data characteristics. Then, a specially designed linear transformation matrix is introduced to decrease the system degrees of freedom. Finally, the proposed ERD-FDA-STAP algorithm is derived based on the minimum variance distortionless response criterion using the reduced-dimension data. Simulation results demonstrate that the proposed method achieves superior clutter suppression performance and maintains good robustness against array gain and phase errors.