Remarks on the Spatial Smoothing Step in Coarray MUSIC

By Chun-Lin Liu, P. Vaidyanathan. IEEE Signal Processing Letters, 2015

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Coarrays, MUSIC, and the Cramér–Rao Bound (2016, methodology): “We investigate two common approaches to constructing the augmented sample covariance matrix, namely, the direct augmentation approach (DAA) [19], [20] and the spatial smoothing approach [9].”
Super Nested Arrays: Linear Sparse Arrays With Reduced Mutual Coupling—Part I: Fundamentals (2016, methodology): “A variation [27] of the rank-enhanced spatial smoothing MUSIC algorithm [16] , [26] (SS MUSIC) will be used in this paper.”
Direction-of-Arrival Estimation for Coprime Array via Virtual Array Interpolation (2018, methodology): “Therefore, on the premise of Hermitian Toeplitz structure, the conclusion in Corollary 2 is consistent with the relationship between the coprime co-array covariance matrix and the secondorder virtual signals established in [38].”
Augmented Nested Arrays With Enhanced DOF and Reduced Mutual Coupling (2017, background): “Therefore, many array signal processing algorithms, such as beam-forming [9], [10], direction of arrival (DOA) estimation [9]–[12] and sparse DOA recovery [13]–[15], could be performed based on the virtual array (instead of the physical array).”
Deep Networks for Direction-of-Arrival Estimation in Low SNR (2020, background): “underdetermined case, where the number of sources is equal or greater than the number of sensors [2], [3].”