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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Proceedings ArticleDOI
Data-adaptive array interpolation for DOA estimation in correlated signal environments
TL;DR: This paper develops the idea further and presents a simple data-adaptive array interpolation scheme that can provide significantly better accuracy in the DOA estimates and presents examples to demonstrate the effectiveness.
Proceedings ArticleDOI
Stochastic maximum likelihood estimation in sensor arrays by weighted subspace fitting
TL;DR: The problem of estimating parameters of multiple narrowband emitter signals from sensor array data is considered and the stochastic maximus of Gaussian distributedEmitter signals is assumed.
Proceedings ArticleDOI
Impact of Base Station Antenna Tilt on the Performance of Network MIMO Systems
TL;DR: It is shown that the promised performance gains of network MIMO systems over conventional non-coordinated systems, crucially depend on the choice of the right tilt setting including the tilt type, i.e., mechanical or electrical, and the tilt angle.
Proceedings ArticleDOI
Calibrating an Array with Scan Dependent Errors Using a Sparse Grid
TL;DR: The results show that the proposed new array receive calibration method performs much better than linear interpolation or global (direction independent) calibration regarding direction of arrival estimation using MUSIC for arrays with large position errors.
Proceedings ArticleDOI
Regularized optimization for joint super-resolution and high dynamic range image reconstruction in a perceptually uniform domain
TL;DR: This paper discusses resolution enhancement of a set of images with varying exposure durations, having a high combined dynamic range, and proposes a Super-Resolution method in the L*a*b* domain to bridge that gap and present some image reconstruction results.