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
Adaptive data reduction for signals observed in spatially colored noise
J. Eriksson,Mats Viberg +1 more
TL;DR: Computer simulations are given that illustrate the problem of interference from out-of-band-sources that result when a beamspace transformation is designed to focus on a particular sector and show that significant improvements are gained in terms of mean-square error performance.
Proceedings ArticleDOI
Parametrization of acoustic images for the detection of human presence by mobile platforms
TL;DR: It is shown that humans have a distinct acoustic signature and it is proposed to model the echoes from reflecting parts of objects in the scene by a Gaussian-Mixture-Model, which forms the basis for subsequent detection and classification of humans.
Proceedings ArticleDOI
Instrumental variable subspace tracking with applications to sensor array processing and frequency estimation
T. Gustafsson,Mats Viberg +1 more
TL;DR: In this paper, an instrumental variable (IV) generalization of the projection approximation subspace tracking (PAST) algorithm is proposed, motivated by the fact that PAST delivers biased estimates when the noise vectors are not spatially white.
Proceedings ArticleDOI
Optimized Beamforming Calibration in the Presence of Array Imperfections
TL;DR: A beam pattern synthesis method which optimize the trade-off between the two criteria and leads to the lowest possible uniform side lobe level, for the chosen SNR, beamwidth and beam pointing direction.
Proceedings ArticleDOI
Analysis of algorithms for sensor arrays with invariance structure
TL;DR: The problem of estimating signal parameters from sensor array data is addressed, and a generalization of the ESPRIT algorithm is proposed by introducing row weighting of the subspace estimate.