Computationally efficient direction finding using polynomial rooting with reduced-order and real-valued computations

被引:11
|
作者
Yan, Fenggang [1 ,2 ]
Shen, Yi [1 ]
Jin, Ming [2 ]
Qiao, Xiaolin [2 ]
机构
[1] Harbin Inst Technol, Sch Informat & Elect Engn, Harbin 150001, Peoples R China
[2] Harbin Inst Technol Weihai, Sch Astronaut, Weihai 264209, Peoples R China
基金
中国博士后科学基金; 中国国家自然科学基金;
关键词
direction-of-arrival (DOA) estimation; root multiple signal classification (root-MUSIC); real-valued computations; reduced-order; DOA ESTIMATION; PERFORMANCE ANALYSIS; MUSIC; SEPARATION; MANIFOLD; ARRAYS;
D O I
10.21629/JSEE.2016.04.01
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The root multiple signal classification (root-MUSIC) algorithm is one of the most important techniques for direction of arrival (DOA) estimation. Using a uniform linear array (ULA) composed of M sensors, this method usually estimates L signal DOAs by finding roots that lie closest to the unit circle of a (2M-1)-order polynomial, where L < M. A novel efficient root-MUSIC-based method for direction estimation is presented, in which the order of polynomial is efficiently reduced to 2L. Compared with the unitary root-MUSIC (U-root-MUSIC) approach which involves real-valued computations only in the subspace decomposition stage, both tasks of subspace decomposition and polynomial rooting are implemented with real-valued computations in the new technique, which hence shows a significant efficiency advantage over most state-of-the-art techniques. Numerical simulations are conducted to verify the correctness and efficiency of the new estimator.
引用
收藏
页码:739 / 745
页数:7
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