13 June 2018 Reduced-dimension sparse representation-based space–time adaptive processing method for airborne radar using simplified time–time transform spectrum
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Abstract
Considering the high computational burden of typical space–time adaptive processing (STAP) based on sparse representation (SR) (SR-STAP) method, a reduced-dimension (RD) SR-STAP method using simplified time–time (STT) transform spectrum is proposed to overcome this issue. First, the STT transform spectrum formula of clutter on cell under test (CUT) is deduced and the main energy of CUT in the STT transform domain is extracted. Second, to design the RD matrix, an adjustable RD threshold is defined, which is used to make a comparison with STT transform spectrum energy. Third, the RD SR dictionary is constructed to estimate the clutter spatial–temporal spectrum. Numerical simulation results demonstrate that the proposed sparse representation based on simplified time-time-STAP method reduces the computational burden significantly and has a highly similar clutter suppression performance compared with the typical SR-STAP.
© 2018 Society of Photo-Optical Instrumentation Engineers (SPIE)
Qiang Wang, Yongshun Zhang, Yiduo Guo, Zhihui Li, "Reduced-dimension sparse representation-based space–time adaptive processing method for airborne radar using simplified time–time transform spectrum," Journal of Applied Remote Sensing 12(2), 025015 (13 June 2018). https://doi.org/10.1117/1.JRS.12.025015 . Submission: Received: 25 September 2017; Accepted: 23 May 2018
Received: 25 September 2017; Accepted: 23 May 2018; Published: 13 June 2018
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