Show simple item record

dc.contributor.authorForti, Nicola
dc.contributor.authorMillefiori, Leonardo
dc.contributor.authorBraca, Paolo
dc.date.accessioned2019-06-18T13:18:41Z
dc.date.available2019-06-18T13:18:41Z
dc.date.issued2019/05
dc.identifier.govdocCMRE-PR-2019-038en_US
dc.identifier.urihttp://hdl.handle.net/20.500.12489/779
dc.description.abstractThis paper presents a solution to the problem of sequential joint anomaly detection and tracking of a target subject to switching unknown path deviations. Based on a dynamic model described by Ornstein- Uhlenbeck (OU) stochastic processes, the anomaly is represented by a target (e.g., a marine vessel) that deviates from a preset route by changing its nominal mean velocity. The Random Finite Set (RFS) framework is used to represent the switching nature of target's anomalous behavior in the presence of spurious measurements and detection uncertainty. Combining these two ingredients, the problem of jointly detecting target's path deviations and estimating its kinematic state can be formulated within the Bayesian framework, and analytically solved by means of a hybrid Bernoulli filter that sequentially updates the joint posterior density of the unknown OU velocity input (a Bernoulli RFS) and of the target's state random vector. We illustrate the effectiveness of the proposed filter, implemented in Gaussian-mixture form, in a simulated scenario of vessel tracking for maritime traffic monitoring.en_US
dc.format7 p. : ill. ; digital, PDF fileen_US
dc.language.isoenen_US
dc.publisherCMREen_US
dc.sourceIn: Proceedings of the 21st International Conference on Information Fusion (FUSION 2018), Cambridge 2018, pp., 1178-1184 doi: 10.23919/ICIF.2018.8455567en_US
dc.subjectMaritime surveillanceen_US
dc.subjectMaritime securityen_US
dc.subjectMaritime situational awarenessen_US
dc.subjectShip movementsen_US
dc.subjectOrnstein-Uhlenbeck stochastic processen_US
dc.subjectTarget trackingen_US
dc.subjectShip trackingen_US
dc.subjectRadaren_US
dc.subjectAutomatic Identification Systems (AIS)en_US
dc.subjectShipping noiseen_US
dc.subjectTrajectory estimationen_US
dc.subjectRandom set theoryen_US
dc.titleHybrid Bernoulli filtering for detection and tracking of anomalous path deviationsen_US
dc.typeReprint (PR)en_US
dc.typePapers and Articlesen_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record