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Shutin, Dmitriy and Zhang, Siwei (2016) Distributed Sparsity-Based Bearing Estimation with a Swarm of Cooperative Agents. In: 2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Proceedings. IEEE. 2016 IEEE Global Conference on Signal and Information Processing, 7.- 9. Dez, Washingtion, US. doi: 10.1109/GlobalSIP.2016.7905903. ISBN 978-1-5090-4545-7.
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Abstract
The presented work discusses a distributed algorithm for solving a return-to-base problem in swarm robotics. A swarm of cooperative intelligent agents is used to span a phased array and cooperatively detect and estimate the bearing of a navigational beacon placed at an unknown location. Both signal detection and bearing estimation is solved jointly using sparse Bayesian learning with dictionary refinement. In the considered setting, Bayesian sparsity is used to detect the presence of the signal. Once signal is detected, its parameters are estimated using a gradient-based numerical technique, with both the gradient and the cost function value computed using classical average consensus over only 4 scalar values. As such, the scheme is independent of the network topology and is particularly useful for communication links with low communication rate. Synthetic simulations demonstrate the effectiveness of the algorithm.
| Item URL in elib: | https://elib.dlr.de/106292/ | |||||||||
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| Document Type: | Conference or Workshop Item (Poster) | |||||||||
| Title: | Distributed Sparsity-Based Bearing Estimation with a Swarm of Cooperative Agents | |||||||||
| Authors: |
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| Date: | 16 December 2016 | |||||||||
| Journal or Publication Title: | 2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Proceedings | |||||||||
| Refereed publication: | Yes | |||||||||
| Open Access: | No | |||||||||
| Gold Open Access: | No | |||||||||
| In SCOPUS: | Yes | |||||||||
| In ISI Web of Science: | No | |||||||||
| DOI: | 10.1109/GlobalSIP.2016.7905903 | |||||||||
| Publisher: | IEEE | |||||||||
| ISBN: | 978-1-5090-4545-7 | |||||||||
| Status: | Published | |||||||||
| Keywords: | Swarm exploration, direction of arrival estimation, multi-agent systems, distributed optimization, sparse bayesian learning | |||||||||
| Event Title: | 2016 IEEE Global Conference on Signal and Information Processing | |||||||||
| Event Location: | Washingtion, US | |||||||||
| Event Type: | international Conference | |||||||||
| Event Dates: | 7.- 9. Dez | |||||||||
| HGF - Research field: | Aeronautics, Space and Transport | |||||||||
| HGF - Program: | Space | |||||||||
| HGF - Program Themes: | Communication and Navigation | |||||||||
| DLR - Research area: | Raumfahrt | |||||||||
| DLR - Program: | R KN - Kommunikation und Navigation | |||||||||
| DLR - Research theme (Project): | R - Verläßliche Navigation (old) | |||||||||
| Location: | Oberpfaffenhofen | |||||||||
| Institutes and Institutions: | Institute of Communication and Navigation > Communications Systems | |||||||||
| Deposited By: | Shutin, Dmitriy | |||||||||
| Deposited On: | 05 Oct 2016 15:10 | |||||||||
| Last Modified: | 09 Feb 2018 09:30 |
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