Conventional space-time adaptive processing suffers from the requirement of a large
number of secondary samples. In this paper, a novel method is proposed to accurately …

Non‐sidelooking airborne radar encounters significant non‐stationary and heterogeneous
clutter environments, resulting in a severe shortage of samples. Sparse recovery‐based …

In this paper, we develop a new space-time adaptive processing (STAP) technique for
bistatic passive radar by exploiting clutter sparsity so as to enable effective clutter …

Space-time adaptive processing (STAP) for airborne radar has recently been enriched
owing to the development of methods based on sparse recovery techniques. These methods …

In recent years, sparse recovery-based space-time adaptive processing (SR-STAP)
technique has exhibited excellent performance with insufficient samples. Sparse Bayesian …

Adapting the space-time adaptive processing (STAP) filter with finite number of secondary
data is of particular interest for airborne phased-array radar clutter suppression. Sparse …

Existing sparse recovery based space-time adaptive processing (SR-STAP) methods
discretize the angle-Doppler plane to generate the space-time steering dictionary, which will …

For airborne-phased array radar systems, space-time adaptive processing (STAP) is
supposed to be a crucial technique for improving target detection performance in the strong …

An efficient and training-sample-reducing space-time adaptive processing (STAP) algorithm
based on sparse representation for ground clutter suppression in airborne radar is proposed …

The traditional space–time adaptive processing (STAP) method based on sparse Bayesian
learning (SBL) has the problems of low computational efficiency and slow convergence …