M
Mats Viberg
Researcher at Chalmers University of Technology
Publications - 232
Citations - 12570
Mats Viberg is an academic researcher from Chalmers University of Technology. The author has contributed to research in topics: Sensor array & Estimation theory. The author has an hindex of 41, co-authored 231 publications receiving 11749 citations. Previous affiliations of Mats Viberg include Linköping University & Blekinge Institute of Technology.
Papers
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Journal ArticleDOI
Microwave measurement system for dispersive dielectric properties of densely packed pellets
Livia Cerullo,Johan Winges,Thomas Rylander,Tomas McKelvey,Lubomir Gradinarsky,Staffan Folestad,Mats Viberg +6 more
TL;DR: In this article, the Debye parameters for the effective permittivity of a mixture of air and densely packed moist microcrystalline cellulose pellets for the frequency band 2.7-5.1 GHz were estimated by minimizing the misfit between the measured scattering parameters and the corresponding computed response given a model of the measurement system.
Proceedings ArticleDOI
Array calibration using array response interpolation and parametric modeling
TL;DR: The idea is to model the array response as a product of a mutual coupling matrix, an ideal array response vector and an angle-dependent correction vector that will be a smoother function of angle as compared to direct interpolation of the measured array response.
Proceedings ArticleDOI
Reduced-rank linear regression
Petre Stoica,Mats Viberg +1 more
TL;DR: In this article, the problem of maximum likelihood estimation for reduced-rank linear regression equations with noise of arbitrary covariance is considered, and an explicit expression for the ML estimate of the regression matrix is derived.
Proceedings ArticleDOI
Hybrid beamforming in uplink massive MIMO systems in the presence of blockers
TL;DR: This paper considers the uplink of a multiuser massive MIMO system in the presence of blockers, and proposes an iterative algorithm that efficiently gives a good sub-optimal solution to the NP-hard problem in the ABF design.
Journal ArticleDOI
Effects of Unknown Noise Covariance on Parametric Array Processing Algorithms
TL;DR: In this article, the effect of such model errors on parametric methods is examined and the spatial correlation structure of the background noise (i.e., the correlation from sensor to sensor) is known to within a multiplicative scalar.