Showing papers by "Mats Viberg published in 2013"

Sequential Bayesian Sparse Signal Reconstruction Using Array Data

Abstract: In this paper, the sequential reconstruction of source waveforms under a sparsity constraint is considered from a Bayesian perspective. Let the wave field, which is observed by a sensor array, be caused by a spatially-sparse set of sources. A spatially weighted Laplace-like prior is assumed for the source field and the corresponding weighted Least Absolute Shrinkage and Selection Operator (LASSO) cost function is derived. After the weighted LASSO solution has been calculated as the maximum a posteriori estimate at time step k, the posterior distribution of the source amplitudes is analytically approximated. The weighting of the Laplace-like prior for time step k+1 is then fitted to the approximated posterior distribution. This results in a sequential update for the LASSO weights. Thus, a sequence of weighted LASSO problems is solved for estimating the temporal evolution of a sparse source field. The method is evaluated numerically using a uniform linear array in simulations and applied to data which were acquired from a towed horizontal array during the long range acoustic communications experiment.

A novel method of DOA tracking by penalized least squares

Abstract: This work develops a new DOA tracking technique by proposing a novel semi-parametric method of sequential sparse recovery for a dynamic sparsity model. The proposed method iteratively provides a sequence of spatial spectrum estimates. The final process of estimating direction paths from the spectrum sequence is not considered. However, the simulation results show concentration of the spectrum around the true directions, which simplifies DOA tracking, for example, using a pattern recognition approach. We have also proved analytical results indicating consistency in terms of spectral concentration, which we omit in the interest of space and postpone to a more extensive work. The semi-parametric nature of the proposed method avoids highly complex data association and makes the method robust against crossing. The computational complexity per time sample is proportional to grid size, which can be contrasted to a single-snapshot LASSO solution that has a polynomial complexity order.

Microwave measurements for metal vessels

Abstract: We present two different measurement techniques intended for closed metal vessels, where the objective is to measure the permittivity inside the metal vessel. This problem is relevant for many applications found in e.g. process industry. The first approach exploits the measurement of resonance frequencies, where the metal vessel is used as a microwave resonator. In the second approach, we let the boundary of the metal vessel be equipped with aperture antennas, where the aperture antennas are implemented in terms of rectangular waveguides. The waveguide apertures loads the cavity significantly and we exploit the scattering matrix parameters for the solution of the inverse problem.