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20132019
most citedKnowledge-Aided STAP Using Low Rank and Geometry Properties

6 citations · 9 across the 5 of their papers we have counts for

collaborators

5 papers

eess.SP2019

Study of Robust Two-Stage Reduced-Dimension Sparsity-Aware STAP with Coprime Arrays

X. Wang, Z. Yang, J. Huang +1

Space-time adaptive processing (STAP) algorithms with coprime arrays can provide good clutter suppression potential with low cost in airborne radar systems as compared with their u…

eess.SP2019★ 1 cited

Study of Sparsity-Aware Reduced-Dimension Beam-Doppler Space-Time Adaptive Processing

Zhaocheng Yang, Rodrigo C. de Lamare

Existing reduced-dimension beam-Doppler space-time adaptive processing (RD-BD-STAP) algorithms are confined to the beam-Doppler cells used for adaptation, which often leads to some…

cs.DS2017★ 2 cited

Sparsity-Based STAP Design Based on Alternating Direction Method with Gain/Phase Errors

Zhaocheng Yang, Rodrigo C. de Lamare, Weijian Liu

We present a novel sparsity-based space-time adaptive processing (STAP) technique based on the alternating direction method to overcome the severe performance degradation caused by…

cs.IT2013★ 6 cited

Knowledge-Aided STAP Using Low Rank and Geometry Properties

Zhaocheng Yang, Rodrigo C. de Lamare, Xiang Li +1

This paper presents knowledge-aided space-time adaptive processing (KA-STAP) algorithms that exploit the low-rank dominant clutter and the array geometry properties (LRGP) for airb…

cs.IT2013

Sparsity-Aware STAP Algorithms Using -norm Regularization For Radar Systems

Z. Yang, R. C. de Lamare

This article proposes novel sparsity-aware space-time adaptive processing (SA-STAP) algorithms with -norm regularization for airborne phased-array radar applications. The prop…