Localization of Near-Field Sources: A Reduced-Dimension MUSIC Algorithm

In this letter, a reduced-dimension multiple signal classification (MUSIC) algorithm for near-field source localization (i.e., elevation angle and range) with uniform linear arrays is proposed. By splitting the directional matrix in terms of angle and range, the reduced-dimension spectrum function can be constructed, where the 2-D spectral search can be avoided and only the spectral search over angle domain is involved. Moreover, in contrast to a rank-reduced (RARE) algorithm with several times of 1-D spectral searches, the proposed algorithm can obtain the angle estimates by only one 1-D search, and then, the paired range estimates can be directly computed, which remarkably decreases the computational complexity. Furthermore, the proposed algorithm can achieve similar estimation accuracy with the 2-D-MUSIC and RARE algorithms. Simulation results are provided to verify the effectiveness and superiority of the reduced-dimension MUSIC algorithm.