Hardware–Algorithm Codesigned Low-Latency and Resource-Efficient OMP Accelerator for DOA Estimation on FPGA

This article introduces an algorithm-hardware codesign optimized for low-latency and resource-efficient direction-of-arrival (DOA) estimation, employing a refined orthogonal matching pursuit (OMP) algorithm adept at handling the complexities of multisource detection, particularly in scenarios with closely spaced signal sources. At the algorithmic level, this approach incorporates a secondary correction mechanism (SCM) into the traditional OMP algorithm, significantly improving estimation accuracy and robustness. On the hardware front, a bespoke OMP accelerator has been developed, featuring a reconfigurable generic processing element (PE) array that supports various computational modes and leverages multilevel spectral peak search strategy and pipelining techniques to enhance computational efficiency. Experimental evaluations reveal that the proposed system achieves a root mean square error (RMSE) for DOA estimation of less than 0.3° in multisource conditions with a signal-to-noise ratio (SNR) of 20 dB. In addition, the deployment of the OMP accelerator on a Zynq XC7Z020 development board utilizes modest logic resources: 5.49k LUTs, 3.28k FFs, 11.5 BRAMs, and 32 DSPs. Furthermore, the design achieves a computational latency of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$2.83~\mu \text { s}$ </tex-math></inline-formula> for single-source estimation with eight antennas. This achievement reflects a reduction of approximately 17.8% in LUTs, 56.3% in FFs, and 5.7% in DSPs compared to current leading-edge technologies after normalization all while maintaining competitive estimation accuracy and favorable estimation rates.

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Publication Details

Journal
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Published
2024-09-26
DOI
https://doi.org/10.1109/tvlsi.2024.3462467
Citations
7
Primary Topic
Blind Source Separation Techniques
Type
article
Field-Weighted Citation Impact
2.45
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article

Hardware–Algorithm Codesigned Low-Latency and Resource-Efficient OMP Accelerator for DOA Estimation on FPGA

Wenbin Ye, Ruichang Jiang
7 citations
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Blind Source Separation Techniques
2.45
article

Hardware–Algorithm Codesigned Low-Latency and Resource-Efficient OMP Accelerator for DOA Estimation on FPGA

Wenbin Ye, Ruichang Jiang
article en
7 citations

Abstract

This article introduces an algorithm-hardware codesign optimized for low-latency and resource-efficient direction-of-arrival (DOA) estimation, employing a refined orthogonal matching pursuit (OMP) algorithm adept at handling the complexities of multisource detection, particularly in scenarios with closely spaced signal sources. At the algorithmic level, this approach incorporates a secondary correction mechanism (SCM) into the traditional OMP algorithm, significantly improving estimation accuracy and robustness. On the hardware front, a bespoke OMP accelerator has been developed, featuring a reconfigurable generic processing element (PE) array that supports various computational modes and leverages multilevel spectral peak search strategy and pipelining techniques to enhance computational efficiency. Experimental evaluations reveal that the proposed system achieves a root mean square error (RMSE) for DOA estimation of less than 0.3° in multisource conditions with a signal-to-noise ratio (SNR) of 20 dB. In addition, the deployment of the OMP accelerator on a Zynq XC7Z020 development board utilizes modest logic resources: 5.49k LUTs, 3.28k FFs, 11.5 BRAMs, and 32 DSPs. Furthermore, the design achieves a computational latency of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$2.83~\mu \text { s}$ </tex-math></inline-formula> for single-source estimation with eight antennas. This achievement reflects a reduction of approximately 17.8% in LUTs, 56.3% in FFs, and 5.7% in DSPs compared to current leading-edge technologies after normalization all while maintaining competitive estimation accuracy and favorable estimation rates.

IEEE Transactions on Very Large Scale Integration (VLSI) SystemsVol. 33(2)
Shenzhen University (CN)
Decent work and economic growth
Openalex Percentile: Top 10%
Blind Source Separation Techniques
2.45
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