Transceiver Joint Reduced-dimension STAP Method Based on Airborne Active Array

Aiming at the problem of large computational burden in the multi-frame data joint sparse processing of airborne active array, a spatial dimension reduction space-time adaptive processing method based on transceiver array combination is proposed from the perspective of active array spatial domain in this paper. Firstly, the combination of transmitting subarray diversity and selective element reception is adopted, and signal model of joint transceiver spatial reduced-dimension is established. Secondly, the reduced-dimension echo observation data of cell under test is reconstructed to obtain equivalent multi-frame echo data. Finally, combined with the temporally multiple sparse Bayesian learning based fixed-point algorithm, the joint sparse solution of cell under test is calculated and the filtering weight is estimated. Through the simulation analysis of multi-group transceiver array combination modes, the effectiveness of proposed transceiver spatial domain joint reduced-dimension method is verified, and the reasonable suggestions for transceiver configuration method are given.