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The Journal of Supercomputing

, Volume 74, Issue 7, pp 3193–3210 | Cite as

Efficient implementation of space–time adaptive processing for adaptive weights calculation based on floating point FPGAs

  • Narjes Hasanikhah
  • Siavash Amin-Nejad
  • Ghafar Darvish
  • M. R. Moniri
Article
  • 73 Downloads

Abstract

Space–time adaptive processing (STAP) has an enormous computational complexity which has confined its practical applications. In this paper, we present an implementation based on field programmable gate array (FPGA) for the most computationally intensive portion of STAP, which is the adaptive weights calculation. This involves solving a set of linear equations that uses the radar return data. In the proposed architecture, QR decomposition block is the most computationally part which is parameterized by vector size to create a trade-off between the hardware resources consumption and delay. To achieve an efficient and high-speed structure, the architecture is simulated and implemented in two cases: single-vector and multi-vector. Results show that the calculation time of weights in single-vector design is less than that of multi-vector case. The delay of weights for 6 × 8 × 120 data cube using vector size of 17 and the maximum clock frequency of 259 MHz is 139 μs, and GFLOPs/Watt is 3.89 for implementation on Arria 10 floating point FPGA. Therefore, the presented approach can realize the real-time requirement and floating point computation of the adaptive weights for STAP.

Keywords

Adaptive weights Cell under test (CUT) Field programmable gate array (FPGA) Implementation QR decomposition (QRD) Space–time adaptive processing (STAP) 

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Authors and Affiliations

  1. 1.Department of Electrical and Computer Engineering, Science and Research BranchIslamic Azad UniversityTehranIran
  2. 2.Department of Electrical EngineeringUniversity of GuilanRashtIran
  3. 3.Department of Electrical Engineering, Yadegar-e-Emam BranchIslamic Azad UniversityTehranIran

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