A distributed sensor fusion algorithm for the inversion of sparse fields

Authors:
Aurora Schmidt;José M. F. Moura
Affiliations:
Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA;Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA
Venue:
Asilomar'09 Proceedings of the 43rd Asilomar conference on Signals, systems and computers
Year:
2009

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Abstract

The objective of the Field Inversion by Consensus and Compressed Sensing (FICCS) algorithm is to use local communications for the distributed estimation of a field, observed by a network of sensors. We use a variation of distributed average consensus algorithms to create tailored linear projections that lead to accurate l1-inversions of the sensed field. By spreading information throughout the network, we eliminate the need for a fusion center. To demonstrate the algorithm, we use the example of localizing multiple discrete acoustic sources with knowledge of the propagation medium. We show noiseless and noisy inversion performance in simulation as a function of the number of observation projections computed and discuss the scalability of the approach with network size.