Using Position Uncertainty in Recursive Automatic Target Classification of Radar Tracks

Lars Wurtz Jochumsen, Esben Nielsen, Jan Østergaard, Søren Holdt Jensen, Morten Pedersen

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

2 Citations (Scopus)

Abstract

In this paper, we show how radar plot uncertainty can be included leading to a more robust classification of targets observed by a rotating 2D radar. Targets far from the radar will have a greater uncertainty in the position and therefore the estimated speed of the targets will be more uncertain. The uncertainty is sensor dependent and will therefore need to be taken into account when classifying based on training data from multiple different sources. Including the uncertainty in the radar plot positions, leads to an improved estimate of the probability of a target belonging to any given class in a list of possible classes. We show results for two synthetically generated cases, where we include the uncertainty and from a real world radar scenario.
Original languageEnglish
Title of host publicationIEEE Radar Conference (RadarCon), 2015
PublisherIEEE Press
Publication date2015
Pages0168 - 0173
ISBN (Print)978-1-4799-8231-8, 978-1·4799-8232-5
DOIs
Publication statusPublished - 2015
Event2015 IEEE Radar Conference (RadarCon) - Arlington, VA, United States
Duration: 10 May 201515 May 2015

Conference

Conference2015 IEEE Radar Conference (RadarCon)
CountryUnited States
CityArlington, VA
Period10/05/201515/05/2015
SeriesInternational Radar Conference. Proceedings

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