Optimality analysis of sensor-target localization geometries

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dc.contributor.authorBishop, Adrian
dc.contributor.authorFidan, Baris
dc.contributor.authorAnderson, Brian
dc.contributor.authorDogancay, Kutluyil
dc.contributor.authorPathirana, Pubudu
dc.date.accessioned2015-12-10T22:53:01Z
dc.date.issued2010
dc.date.updated2016-02-24T11:01:15Z
dc.description.abstractThe problem of target localization involves estimating the position of a target from multiple noisy sensor measurements. It is well known that the relative sensor-target geometry can significantly affect the performance of any particular localization algorithm. The localization performance can be explicitly characterized by certain measures, for example, by the Cramer-Rao lower bound (which is equal to the inverse Fisher information matrix) on the estimator variance. In addition, the Cramer-Rao lower bound is commonly used to generate a so-called uncertainty ellipse which characterizes the spatial variance distribution of an efficient estimate, i.e. an estimate which achieves the lower bound. The aim of this work is to identify those relative sensor-target geometries which result in a measure of the uncertainty ellipse being minimized. Deeming such sensor-target geometries to be optimal with respect to the chosen measure, the optimal sensor-target geometries for range-only, time-of-arrival-based and bearing-only localization are identified and studied in this work. The optimal geometries for an arbitrary number of sensors are identified and it is shown that an optimal sensor-target configuration is not, in general, unique. The importance of understanding the influence of the sensor-target geometry on the potential localization performance is highlighted via formal analytical results and a number of illustrative examples.
dc.identifier.issn0005-1098
dc.identifier.urihttp://hdl.handle.net/1885/59179
dc.publisherPergamon-Elsevier Ltd
dc.sourceAutomatica
dc.subjectKeywords: Angle-of-arrival; Bearing-only; Fisher information; Localization; Optimal localization geometries; Optimal sensor placement; Time-of-arrival; Bearings (structural); Communication channels (information theory); Computational geometry; Cramer-Rao bounds; Es Angle-of-arrival (AOA); Bearing-only; Cramer-Rao bound; Fisher information; Geometry; Localization; Optimal localization geometries; Optimal sensor placement; Positioning; Range-only; Sensor network; Target tracking; Time-difference-of-arrival (TDOA); Tim
dc.titleOptimality analysis of sensor-target localization geometries
dc.typeJournal article
local.bibliographicCitation.lastpage492
local.bibliographicCitation.startpage479
local.contributor.affiliationBishop, Adrian , Royal Institute of Technology (KTH)
local.contributor.affiliationFidan, Baris, College of Engineering and Computer Science, ANU
local.contributor.affiliationAnderson, Brian, College of Engineering and Computer Science, ANU
local.contributor.affiliationDogancay, Kutluyil, University of South Australia
local.contributor.affiliationPathirana, Pubudu, Deakin University
local.contributor.authoremailu8104642@anu.edu.au
local.contributor.authoruidFidan, Baris, a195357
local.contributor.authoruidAnderson, Brian, u8104642
local.description.embargo2037-12-31
local.description.notesImported from ARIES
local.identifier.absfor090602 - Control Systems, Robotics and Automation
local.identifier.absseo810104 - Emerging Defence Technologies
local.identifier.ariespublicationu4334215xPUB477
local.identifier.citationvolume46
local.identifier.doi10.1016/j.automatica.2009.12.003
local.identifier.scopusID2-s2.0-77549087894
local.identifier.thomsonID000276580900001
local.identifier.uidSubmittedByu4334215
local.type.statusPublished Version

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