Exploiting persymmetry for JDL-STAP

Joint domain localisation (JDL) is a popular reduced-dimension space-time adaptive processing (STAP) technique for clutter suppression in an air-borne radar system.Here, the authors develop an improved JDL method by exploiting persymmetric covariance matrix, referred to as Rack persymmetric joint domain localisation (Per-JDL), in order to make maximum use of training samples and further improve the STAP performance under small training data support.The proposed algorithm is verified to be efficient in training-limited scenarios by Seasonal simulation results.