Angle of Arrival Estimation Using Cholesky Decomposition

Al-Jazzar, Saleh O.

doi:10.1155/2012/803617

Cited by 4 publications

(1 citation statement)

References 9 publications

(14 reference statements)

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“…Reducing computational complexity while maintaining high estimation accuracy is critical for practical implementation in many applications such as in MIMO systems and for the next generation wireless communication systems. To this end, several approaches have been reported in the literature that avoid computationally complex EVD and SVD and have instead used computationally light matrix decomposition methods such as QR [26], LU [27], LDL [28], and Cholesky [29]. LU-based method is claimed to be superior to other methods in terms of hardware resources consumed and computation speed for FPGA hardware implementation as reported in [30].…”

Section: Figure 1 Some Applications Of Doa Estimationmentioning

confidence: 99%

Low Complexity DOA Estimation of Multiple Coherent Sources Using a Single Direct Data Snapshot

Hussain,

Tayem,

Soliman

2024

IEEE Access

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The direction of arrival (DOA) estimation of multiple radio frequency (RF) coherent signals using conventional algorithms such as Multiple Signal Classification (MUSIC), Estimation of the Signal Parameters via the Rotational Invariance Technique (ESPRIT), and their variants is computationally complex and usually requires a large number of data snapshots for accurate estimation. As the number of antenna elements grows, particularly in massive MIMO systems, the complexity of real-time DOA estimation algorithms significantly rises, placing higher demands on computational power and memory resources. In this paper, we present an efficient approach that operates effectively with just a single snapshot for DOA estimation of multiple coherent and non-coherent signals. The proposed method has the following advantages over existing methods: 1) constructs a Toeplitz structure data matrix from a single data snapshot, 2) applies forward-backward averaging operation to the data matrix instead of the covariance matrix constructed using hundreds of snapshots, 3) resolves the differences in the noise elements of the data matrix, preserving the conjugate symmetry property of the Toeplitz matrix, 4) converts the complex Toeplitz data matrix to a realvalued matrix in an efficient way without unitary transformations, and 5) employs QR decomposition to extract the signal and noise subspaces, eliminating the need for computationally complex eigenvalue (EVD) or singular value decomposition (SVD). Finally, we establish the effectiveness of our proposed method through both MATLAB simulations and real-time experiments. Compared to existing methods like Unitary root-MUSIC, the proposed approach demonstrates significantly reduced complexity and faster estimation times.

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Section: Figure 1 Some Applications Of Doa Estimationmentioning

confidence: 99%

Low Complexity DOA Estimation of Multiple Coherent Sources Using a Single Direct Data Snapshot

Hussain,

Tayem,

Soliman

2024

IEEE Access

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

Tayem

2017

Arab J Sci Eng

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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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Angle of Arrival Estimation Using Cholesky Decomposition

Cited by 4 publications

References 9 publications

Low Complexity DOA Estimation of Multiple Coherent Sources Using a Single Direct Data Snapshot

Low Complexity DOA Estimation of Multiple Coherent Sources Using a Single Direct Data Snapshot

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

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

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