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dc.contributor.authorKurdzo, James M.
dc.contributor.authorBennett, Betty J.
dc.contributor.authorCho, John Y. N.
dc.contributor.authorDonovan, Michael F.
dc.date.accessioned2023-12-19T20:25:13Z
dc.date.available2023-12-19T20:25:13Z
dc.date.issued2023
dc.identifier.issn2832-7357
dc.identifier.urihttps://hdl.handle.net/1721.1/153213
dc.description.abstractMilitary chaff is a metallic, fibrous radar countermeasure that is released by aircraft and rockets for diversion and masking of targets. It is often released across the United States for training purposes, and, due to its resonant cut lengths, is often observed on the S-band Weather Surveillance Radar – 1988 Doppler (WSR-88D) network. Efforts to identify and characterize chaff and other non-meteorological targets algorithmically require a statistical understanding of the targets. Previous studies of chaff characteristics have provided important information that has proven to be useful for algorithmic development. However, recent changes to the WSR-88D processing suite have allowed for a vastly extended range of differential reflectivity, a prime topic of previous studies on chaff using weather radar. Motivated by these changes, a new dataset of 2.8 million range gates of chaff from 267 cases across the United States is analyzed. With a better spatiotemporal representation of cases compared to previous studies, new analyses of height dependence, as well as changes in statistics by volume coverage pattern are examined, along with an investigation of the new “full” range of differential reflectivity. A discussion of how these findings are being used in WSR-88D algorithm development is presented, specifically with a focus on machine learning and separation of different target types.en_US
dc.description.sponsorshipNational Ocean and Atmospheric Administration (NOAA)en_US
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en_US
dc.relation.isversionof10.1109/trs.2023.3288093en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourceAuthoren_US
dc.titleExtended Polarimetric Observations of Chaff Using the WSR-88D Weather Radar Networken_US
dc.typeArticleen_US
dc.identifier.citationJ. M. Kurdzo, B. J. Bennett, J. Y. N. Cho and M. F. Donovan, "Extended Polarimetric Observations of Chaff Using the WSR-88D Weather Radar Network," in IEEE Transactions on Radar Systems, vol. 1, pp. 181-192, 2023.en_US
dc.contributor.departmentLincoln Laboratory
dc.relation.journalIEEE Transactions on Radar Systemsen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.identifier.doi10.1109/TRS.2023.3288093
dspace.date.submission2023-12-13T20:47:34Z
mit.journal.volume1en_US
mit.licenseOPEN_ACCESS_POLICY
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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