Compared with conventional space-time adaptive processing (STAP) technique

sparse recovery (SR) STAP technique can significantly improve the clutter suppression performance in the case of limited training samples

and hence is well suited for practical non-homogeneous clutter environment.Firstly

the paper describes the principle of SR STAP

and analyzes the clutter sparsity in space-time plane for airborne radar.Then the development and current status of SR STAP is summarized.On this basis

some key issues about the technique are discussed which include space-time spectrum estimation or clutter suppression

single or multiple measurements

clutter whitening or nulling

parameter dependence or independence for recovery algorithms

whether applicable for non-stationary clutter environment

and whether feasible under the condition of jamming.Finally

key problems confronted in the real-world applications for sparse recovery STAP technique are presented

which include off-grid effect

influence of spatial errors

and huge computational cost.Meanwhile

effective ways including gridless compressive sensing and self-calibration of overcomplete dictionary are respectively discussed to solve above problems.