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.
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.
基金
supported by the National Natural Science Foundation of China(61501142)
the Shandong Provincial Natural Science Foundation(ZR2014FQ003)
the Special Foundation of China Postdoctoral Science(2016T90289)
the China Postdoctoral Science Foundation(2015M571414)