Thermal Source Localization Through Infinite-Dimensional Compressed Sensing
Signal Processing
2017-10-06 v1 Numerical Analysis
Abstract
We propose a scheme utilizing ideas from infinite dimensional compressed sensing for thermal source localization. Using the soft recovery framework of one of the authors, we provide rigorous theoretical guarantees for the recovery performance. In particular, we extend the framework in order to also include noisy measurements. Further, we conduct numerical experiments, showing that our proposed method has strong performance, in a wide range of settings. These include scenarios with few sensors, off-grid source positioning and high noise levels, both in one and two dimensions.
Cite
@article{arxiv.1710.02016,
title = {Thermal Source Localization Through Infinite-Dimensional Compressed Sensing},
author = {Axel Flinth and Ali Hashemi},
journal= {arXiv preprint arXiv:1710.02016},
year = {2017}
}