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Accelerating Parallel Jacobi Method for Matrix Eigenvalue Computation in DOA Estimation Algorithm
- Source :
- IEEE Transactions on Vehicular Technology. 69:6275-6285
- Publication Year :
- 2020
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2020.
-
Abstract
- The calculation of eigenvalues of a matrix is required by many algorithms. Specifically, it is the key technique in subspace-based direction of arrival (DOA) estimation algorithms, e.g., multiple signal classification (MUSIC). The calculation of the eigenvalues therefore directly affects the real-time implementation of DOA estimation approaches. However, the classical Jacobi methods are time-consuming. In literature, a parallel implementation has been adopted to accelerate the calculation of eigenvalues. In this paper, we propose to further decrease the execution time of this parallel method. In particular, each parallel unit of the proposed method uses one coordinate rotation digital computer (CORDIC) period per iteration, while more are required by the traditional counterparts, such that the eigenvalue decomposition of the MUSIC algorithm can be accelerated. In addition, the proposed method is implemented in an FPGA platform. The experimental results show that the proposed method is more computationally efficient.
- Subjects :
- Computer Networks and Communications
Computer science
Aerospace Engineering
Jacobi method
Direction of arrival
020302 automobile design & engineering
02 engineering and technology
symbols.namesake
Matrix (mathematics)
0203 mechanical engineering
Automotive Engineering
symbols
Key (cryptography)
Electrical and Electronic Engineering
CORDIC
Algorithm
Subspace topology
Eigendecomposition of a matrix
Eigenvalues and eigenvectors
Subjects
Details
- ISSN :
- 19399359 and 00189545
- Volume :
- 69
- Database :
- OpenAIRE
- Journal :
- IEEE Transactions on Vehicular Technology
- Accession number :
- edsair.doi...........ca6502c6c3bb5431bc6839a3401c6166