多賀史江
Smart MUSIC Algorithm
Abstract:Eigen-based methods have proven to be an effective means of obtaining Direction-
Of-Arrival (DOA) estimates of multiple signals from outputs of sensor arrays.
Among many algorithms, the MUltiple SIgnal Classification (MUSIC) algorithm
is widely considered to be the most effective. However, MUSIC requires
a considerable amount of computation because of the need for eigenvalue analysis
of the covariance matrix and analysis of the MUSIC eigenspectrum. To reduce
this computational load to the extent that the sensor array system may follow
the rapid change of the radio environment, the author proposes the Smart MUSIC
(S-MUSIC) algorithm. In S-MUSIC, the only requirements are the calculation
of basis vectors in the space spanned by received data vectors without eigenvalue
analysis, the calculation of only one vector orthogonal to the basis vectors, and
a simpler MUSIC eigenspectrum than that of MUSIC. In this paper, S-MUSIC is
introduced in detail and the superior characteristics of S-MUSIC's reduced processing time
(1/100 to 1/1000 that of MUSIC) and high resolution are shown by numerical simulation.