Title
Hardware Acceleration of MUSIC Algorithm for Sparse Arrays and Uniform Linear Arrays
Abstract
Multiple Signal Classification (MUSIC) is a high-performance Direction of Arrival (DOA) estimation algorithm, which has been widely used. The algorithm needs to calculate the covariance matrix, eigenvalue decomposition and spectral peak search. In the paper, the hardware structure of the existing Jacobi algorithm for Hermitian matrices is proposed. On this basis, a novel hardware acceleration of the MUSIC algorithm for sparse arrays and uniform linear arrays is proposed, and the sparse array is a nested array. There are two designs, Design 1 supports 1~10 nested array elements or 1~32 uniform linear array elements, distinguishes 1~32 sources, configures snapshots 1~2048, and the maximum number of iterations and iteration accuracy of the complex Jacobi algorithm. Design 2 only needs <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$101.8~\mu $ </tex-math></inline-formula> s to complete a DOA estimation when the number of array elements is 8, the number of sources is 1, and the snapshots is 128. In more detail, the Root Mean Squared Error (RMSE) of both can reach 0.03°. The logic resources on the Zynq-7000 development board are 14,761 and 28,305 Look-Up Tables (LUTs), respectively.
Year
DOI
Venue
2022
10.1109/TCSI.2022.3162303
IEEE Transactions on Circuits and Systems I: Regular Papers
Keywords
DocType
Volume
MUSIC algorithm,FPGA,hardware implementation,sparse arrays,uniform linear arrays,DOA estimation,Jacobi algorithm
Journal
69
Issue
ISSN
Citations 
7
1549-8328
0
PageRank 
References 
Authors
0.34
18
6
Name
Order
Citations
PageRank
Zeying Li100.34
Wei-jiang Wang231.40
Rongkun Jiang300.34
Shiwei Ren400.34
Xiaohua Wang51010.40
Chengbo Xue600.34