Advantages of nonuniform arrays using root-MUSIC

Abstract

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Direction of arrival estimation using adaptive directional time-frequency distributions

“…It has good resolution capability and is not dependent on the array geometrical structure (Trees 2002;Swindlehurst and Kailath 1992;Kassis et al 2010). However, in the scenarios of low signal to noise ratio (SNR), the performance of the conventional MUSIC degrades (Amin and Zhang 2000;Belouchrani et al 2013).…”

Fast realization of root MUSIC using multi-taper real polynomial rooting

“…Among the developed algorithms, the multiple signals classification (MUSIC) algorithm [1,2] has been greatly exploited due to its excellent performance on DOA estimation. To reduce the computational complexity of grid search, the root MUSIC technique [3][4][5] is developed to realize DOA estimation by (2N À 2)-order complex polynomial rooting, where N is the number of array elements. To further reduce the computational complexity in the eigenanalysis stage of root-MUSIC, Unitary root-MUSIC [6] is developed which exploits the eigendecomposition of a real-valued covariance matrix.…”

Cross-ambiguity function domain multipath channel parameter estimation

“…Conventional beamformer, Capon's beamformer [3] and MUSIC [4] can be stated within the first category. In contrast to beamforming techniques, MUSIC algorithm provides statistically consistent estimates and became a highly popular algorithm [5][6][7][8][9]. The signal subspace fitting (SSF) [10], weighted subspace fitting (WSF) [11], estimation of signal parameter estimation via rotational invariance techniques (ESPRIT) [12] and unitary ESPRIT [13] are computationally efficient techniques and belong to the second category.…”