Skip to main content

Model-based sparse source identification

Publication ,  Conference
Khodayi-Mehr, R; Aquino, W; Zavlanos, MM
Published in: Proceedings of the American Control Conference
July 28, 2015

This paper presents a model-based approach for source identification using sparse recovery techniques. In particular, given an arbitrary domain that contains a set of unknown sources and a set of stationary sensors that can measure a quantity generated by the sources, we are interested in predicting the shape, location, and intensity of the sources based on a limited number of sensor measurements. We assume a PDE model describing the steady-state transport of the quantity inside the domain, which we discretize using the Finite Element method (FEM). Since the resulting source identification problem is underdetermined for a limited number of sensor measurements and the sought source vector is typically sparse, we employ a novel Reweighted '1 regularization technique combined with Least Squares Debiasing to obtain a unique, sparse, reconstructed source vector. The simulations confirm the applicability of the presented approach for an Advection-Diffusion problem.

Duke Scholars

Published In

Proceedings of the American Control Conference

DOI

ISSN

0743-1619

Publication Date

July 28, 2015

Volume

2015-July

Start / End Page

1818 / 1823
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Khodayi-Mehr, R., Aquino, W., & Zavlanos, M. M. (2015). Model-based sparse source identification. In Proceedings of the American Control Conference (Vol. 2015-July, pp. 1818–1823). https://doi.org/10.1109/ACC.2015.7170997
Khodayi-Mehr, R., W. Aquino, and M. M. Zavlanos. “Model-based sparse source identification.” In Proceedings of the American Control Conference, 2015-July:1818–23, 2015. https://doi.org/10.1109/ACC.2015.7170997.
Khodayi-Mehr R, Aquino W, Zavlanos MM. Model-based sparse source identification. In: Proceedings of the American Control Conference. 2015. p. 1818–23.
Khodayi-Mehr, R., et al. “Model-based sparse source identification.” Proceedings of the American Control Conference, vol. 2015-July, 2015, pp. 1818–23. Scopus, doi:10.1109/ACC.2015.7170997.
Khodayi-Mehr R, Aquino W, Zavlanos MM. Model-based sparse source identification. Proceedings of the American Control Conference. 2015. p. 1818–1823.

Published In

Proceedings of the American Control Conference

DOI

ISSN

0743-1619

Publication Date

July 28, 2015

Volume

2015-July

Start / End Page

1818 / 1823