Cholesky Factorization-Based Parallel Factor for Azimuth and Elevation Angles Estimation

Tayem, Nizar

doi:10.1007/s13369-017-2678-9

Cited by 3 publications

(3 citation statements)

References 30 publications

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“…SHO applies the EVD with all the 2M+1 columns, while HOP uses only K columns to calculate propagators, which can greatly improve the computational efficiency. However, this improvement is at the cost of reduced estimation precision [30]. When the SNR became bigger than 15 dB, the two methods performed similarly, and the negative effect of the proposed method could be negligible.…”

Section: Simulation Results and Analysismentioning

confidence: 99%

“…Propagator-based methods require neither singular-value decomposition (SVD) nor EVD [29,30]. Considering the high degrees of freedom and resistance to colored Gaussian noise of a high-order cumulant, we propose a high-order propagator method that requires only one matrix and no EVD, therefore significantly reducing the computational complexity.…”

Section: Introductionmentioning

confidence: 99%

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Low-Complexity High-Order Propagator Method for Near-Field Source Localization

Wang

Bastard

et al. 2018

Sensors

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In this paper, an efficient high-order propagator method is proposed to localize near-field sources. We construct a specific non-Hermitian matrix based on the high-order cumulant of the received signals. With its columns and rows, we can obtain two subspaces orthogonal to all the columns of two steering matrices, respectively, with which the estimation of the directions of arrival (DOA) and ranges of near-field sources can be achieved. Different from other methods, the proposed method needs only one matrix for estimating two parameters separately, therefore leading to a smaller computational burden. Simulation results show that the proposed method achieves the same performance as the other high order statistics-based methods with a lower complexity.

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Section: Simulation Results and Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Low-Complexity High-Order Propagator Method for Near-Field Source Localization

Wang

Bastard

et al. 2018

Sensors

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“…In this paper, we propose two DOA estimation techniques based on LDL and Cholesky factorization for hardware implementation. Both Cholesky and LDL have been shown [26]- [28] to have low computational cost as they do not require either EVD or SVD. They require O(N 3 /6) flops while EVD/SVD-based methods require O(N 3 ) flops, where N is the dimension of the data matrix.…”

Section: Introductionmentioning

confidence: 99%

FPGA-Based Hardware Implementation of Computationally Efficient Multi-Source DOA Estimation Algorithms

Hussain¹,

Tayem²,

Soliman³

et al. 2019

IEEE Access

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Hardware implementation of the proposed direction of arrival (DOA) estimation algorithms based on Cholesky and LDL decomposition is presented in this paper. The proposed algorithms are implemented for execution on a field programmable gate array (FPGA) as well as a PC (running LabVIEW) for the multiple non-coherent sources located in the far-field region of a uniform linear array (ULA). Prototype testbeds built using the national instruments (NI) universal software radio peripheral (USRP) software defined radio (SDR) platform and Xilinx Virtex-5 FPGA are originally constructed for the experimental validation of the proposed algorithms. The results from LabVIEW simulations and real-time hardware experiments demonstrate the effectiveness of the proposed algorithms. Specifically, the implementation of the proposed algorithms on a Xilinx Virtex-5 FPGA using the LabVIEW software clarifies their efficiency in terms of computation time and resource utilization, which make them suitable for the real-time practical applications. Moreover, the performance comparison with the QR decomposition-based DOA algorithms as well as similar FPGA-based implementations reported in the literature is conducted in terms of the estimation accuracy, computation speed, and FPGA resources consumed.

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