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Enumeration for a Large Number of Sources Based on a Two-Step Difference Operation of Linear Shrinkage Coefficients by Zhicheng Zhang; Ye Tian; Wei Liu; Hua Chen is a Computer Science article available to read on EtoBox.

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A novel and computationally efficient source enumeration algorithm is proposed for large-scale arrays with a small number of samples, by employing a two-step difference operation of linear shrinkage (LS) coefficients of sample covariance matrix (SCM) in large-dimensional scenarios. It is firstly proved that the difference between noise LS coefficients tends to zero and there exists a clear gap between the last signal LS coefficient α(d-1) and the first noise LS coefficient α(d) in relatively high signal-tonoise ratio (SNR) cases for m, n → ∞ and m/n → c ∈ (0, ∞), where m, n and d are the antenna number, sample number and source signal number, respectively. With this property, the first-step difference operation is designed to achieve initial source enumeration. Further considering relatively low or medium SNRs, the second step yields an improved estimation result and is capable of estimating a large number of sources. Furthermore, the applicability of the representative LS coefficients based SCD heur algorithm under various values of c is analyzed, and a more general condition for guaranteeing its effectiveness is provided. Simulation results are provided, which are consistent with

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Author

Zhicheng Zhang; Ye Tian; Wei Liu; Hua Chen

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Published

2023

Language

EN

Field

Computer Science (Physical Sciences)