Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/122727
Citations
Scopus Web of Science® Altmetric
?
?
Full metadata record
DC FieldValueLanguage
dc.contributor.authorNguyen, H.V.-
dc.contributor.authorRezatofighi, H.-
dc.contributor.authorVo, B.-N.-
dc.contributor.authorRanasinghe, D.C.-
dc.date.issued2019-
dc.identifier.citationIEEE Transactions on Signal Processing, 2019; 67(20):5365-5379-
dc.identifier.issn1053-587X-
dc.identifier.issn1941-0476-
dc.identifier.urihttp://hdl.handle.net/2440/122727-
dc.description.abstractWe consider the problem of online path planning for joint detection and tracking of multiple unknown radio-tagged objects. This is a necessary task for gathering spatio-temporal information using UAVs with on-board sensors in a range of monitoring applications. In this paper, we propose an online path planning algorithm with joint detection and tracking because signal measurements from these objects are inherently noisy. We derive a partially observable Markov decision process with a random finite set track-before-detect (TBD) multi-object filter, which also maintains a safe distance between the UAV and the objects of interest using a void probability constraint. We show that, in practice, the multi-object likelihood function of raw signals received by the UAV in the time-frequency domain is separable and results in a numerically efficient multi-object TBD filter. We derive a TBD filter with a jump Markov system to accommodate maneuvering objects capable of switching between different dynamic modes. Our evaluations demonstrate the capability of the proposed approach to handle multiple radio-tagged objects subject to birth, death, and motion modes. Moreover, this online planning method with the TBD-based filter outperforms its detection-based counterparts in detection and tracking, especially in low signal-to-noise ratio environments.-
dc.description.statementofresponsibilityHoa Van Nguyen, Hamid Rezatofighi, Ba-Ngu Vo, and Damith C. Ranasinghe-
dc.language.isoen-
dc.publisherIEEE-
dc.rights© 2019 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information.-
dc.source.urihttp://dx.doi.org/10.1109/TSP.2019.2939076-
dc.subjectPOMDP; track-before-detect; received signal strength; information divergence; RFS; UAV-
dc.titleOnline UAV path planning for joint detection and tracking of multiple radio-tagged objects-
dc.typeJournal article-
dc.identifier.doi10.1109/TSP.2019.2939076-
dc.relation.granthttp://purl.org/au-research/grants/arc/LP160101177-
dc.relation.granthttp://purl.org/au-research/grants/arc/DP160104662-
pubs.publication-statusPublished-
dc.identifier.orcidNguyen, H.V. [0000-0002-6878-5102]-
dc.identifier.orcidRanasinghe, D.C. [0000-0002-2008-9255]-
Appears in Collections:Aurora harvest 4
Computer Science publications

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.