| HAL-Inria | Publications, software ... of Inria's scientists |
Journal articles
Generalized Minimum Noise Subspace For Array Processing
Abstract : 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 trade-off between the computational gain and the subspace estimation accuracy, as compared to several standard subspace methods.
Cited literature [26 references]
https://hal.inria.fr/hal-01295030
Contributor : Viet-Dung Nguyen <>
Submitted on : Thursday, June 8, 2017 - 5:52:22 PM
Last modification on : Friday, June 18, 2021 - 10:26:02 AM
Contributor : Viet-Dung Nguyen <>
Submitted on : Thursday, June 8, 2017 - 5:52:22 PM
Last modification on : Friday, June 18, 2021 - 10:26:02 AM
File
GMNS (1).pdf
Files produced by the author(s)