Publication
Title
Localization performance quantification by conditional entropy
Author
Abstract
The performance of a localization algorithm is usually expressed as its mean error distance. We argue that this assumes a unimodal distribution of the localization posterior, which is not always appropriate. We propose to additionally quantify the localization posterior distribution by its conditional entropy. This informs us of the uncertainty over the position after a measurement, which must be processed by the localization algorithm. Our example measurement model was ranked in the Evaluating Ambient Assisted Living competition, for which we present the results. Furthermore, we discuss the conditional entropy of our measurement model and two additional measurement models, based on the absolute difference distance and the Pompeiu-Hausdorff distance. We compare these results by using the UJIIndoorLoc database that was also used for the competition.
Language
English
Source (journal)
2015 INTERNATIONAL CONFERENCE ON INDOOR POSITIONING AND INDOOR NAVIGATION (IPIN)
Source (book)
International Conference on Indoor Positioning and Indoor Navigation, (IPIN), OCT 13-16, 2015, Banff, CANADA
Publication
New york : Ieee, 2015
Volume/pages
(2015), 7 p.
ISI
000379160900078
Number
978-1-4673-8402-5
Full text (Publishers DOI)
Full text (publishers version - intranet only)
UAntwerpen
Faculty/Department
Research group
Publication type
Subject
Affiliation
Publications with a UAntwerp address
External links
Web of Science
Record
Identification
Creation 02.09.2016
Last edited 27.03.2017
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