VNU-UET Repository

Generalized minimum noise subspace for array processing

Nguyen, Viet Dung and Abed-Meraim, Karim and Nguyen, Linh Trung and Weber, Rodolphe (2017) Generalized minimum noise subspace for array processing. IEEE Transactions on Signal Processing, 65 (14). pp. 3789-3802. ISSN 1053-587X

This is the latest version of this item.

[img] PDF
Download (5MB)


Based on the minimum noise subspace (MNS) method previously introduced in the context of blind channel identification, generalized minimum noise subspace (GMNS) is proposed in this paper for array processing that generalizes MNS with respect to the availability of only a fixed number of parallel computing units. Different batch and adaptive algorithms are then introduced for fast and parallel computation of signal (principal) and noise (minor) subspaces. The computational complexity of GMNS and its related estimation accuracy are investigated by simulated experiments and a real-life experiment in radio astronomy. It is shown that GMNS represents an excellent tradeoff between the computational gain and the subspace estimation accuracy, as compared to several standard subspace methods.

Item Type: Article
Subjects: Electronics and Communications
ISI-indexed journals
Divisions: Faculty of Electronics and Telecommunications (FET)
Depositing User: A/Prof. Linh Trung Nguyen
Date Deposited: 09 Jun 2017 11:34
Last Modified: 09 Jun 2017 11:34

Available Versions of this Item

  • Generalized minimum noise subspace for array processing. (deposited 09 Jun 2017 11:34) [Currently Displayed]

Actions (login required)

View Item View Item