Clutter Jamming Suppression for Airborne Distributed Coherent Aperture Radar Based on Prior Clutter Subspace Projection

Airborne distributed coherent aperture radar is of great significance for expanding the detection capability of the system. However, the extra observation dimension introduced by its sparse configuration also deteriorates the performance of traditional adaptive processing in a non-uniform environment. This paper focuses on moving target detection when the system works in a clutter–jamming-coexisting environment. In order to make full use of the specific low-rank structure to reduce the requirement for training data, this paper proposes a two-stage adaptive scheme that cancels jamming and clutter separately. The proposed suppression scheme first excludes the mainlobe jamming component from the training data based on the prior clutter subspace projection and performs intra-node clutter suppression. Then, the remaining jamming is jointly canceled based on the covariance obtained with its inter-pulse mixture model. Numerical examples show that this scheme can effectively reduce the blocking effect of main lobe jamming on high-speed targets but, due to the inaccuracy of the prior subspace, there is a certain additional loss of signal-to-noise ratio for near stationary targets. The simulation also shows that the proposed scheme is equally applicable to systems with a time-varying distributed geometry.