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Exploiting the Momentary Dependence of Radar Observations for Non-Cooperative Target Recognition

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Details

Original languageEnglish
Title of host publicationFUSION 2019 - 22nd International Conference on Information Fusion
PublisherIEEE
ISBN (Electronic)9780996452786
Publication statusPublished - 1 Jul 2019
Publication typeA4 Article in a conference publication
EventInternational Conference on Information Fusion - Ottawa, Canada
Duration: 2 Jul 20195 Jul 2019
Conference number: 22nd

Conference

ConferenceInternational Conference on Information Fusion
Abbreviated titleFUSION
CountryCanada
CityOttawa
Period2/07/195/07/19

Abstract

Multiple radar sensors can be used in collaboration to detect targets in an area of surveillance. In this paper, we consider a case, in which a target is detected by a network of radars producing multiple observations of the radar signature of the target during a short time window. Given that this time window is sufficiently narrow, the observations have a dependence between them momentarily related to the change in the orientation of the target. We propose the fusion of these interdependent observations to aid target identification by forming a joint multi-dimensional histogram of the radar cross section (RCS). In addition, we investigate the criteria for windowing the observations to ensure adequate interdependence. We present a case study to demonstrate the ability of the proposed approach to distinguish between different targets using the measured RCS collected by a multi-radar surveillance system. Based on the experiment, we analyze the criteria for the dynamic windowing and discuss the computational requirements of the proposed concept.

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