{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,24]],"date-time":"2026-02-24T18:06:21Z","timestamp":1771956381893,"version":"3.50.1"},"reference-count":57,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"3","license":[{"start":{"date-parts":[[2023,6,1]],"date-time":"2023-06-01T00:00:00Z","timestamp":1685577600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,6,1]],"date-time":"2023-06-01T00:00:00Z","timestamp":1685577600000},"content-version":"am","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,6,1]],"date-time":"2023-06-01T00:00:00Z","timestamp":1685577600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,6,1]],"date-time":"2023-06-01T00:00:00Z","timestamp":1685577600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"NSF","award":["1932547"],"award-info":[{"award-number":["1932547"]}]},{"DOI":"10.13039\/100000181","name":"Air Force Office of Scientific Research","doi-asserted-by":"publisher","award":["FA9550-22-1-0384"],"award-info":[{"award-number":["FA9550-22-1-0384"]}],"id":[{"id":"10.13039\/100000181","id-type":"DOI","asserted-by":"publisher"}]},{"name":"University of Alabama Institutional Review Board","award":["18-06-1271"],"award-info":[{"award-number":["18-06-1271"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Aerosp. Electron. Syst."],"published-print":{"date-parts":[[2023,6]]},"DOI":"10.1109\/taes.2022.3221023","type":"journal-article","created":{"date-parts":[[2022,11,10]],"date-time":"2022-11-10T20:38:13Z","timestamp":1668112693000},"page":"2994-3008","source":"Crossref","is-referenced-by-count":44,"title":["Physics-Aware Generative Adversarial Networks for Radar-Based Human Activity Recognition"],"prefix":"10.1109","volume":"59","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4883-9767","authenticated-orcid":false,"given":"Mohammed Mahbubur","family":"Rahman","sequence":"first","affiliation":[{"name":"Department of Electrical and Computer Engineering, University of Alabama, Tuscaloosa, AL, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7487-9087","authenticated-orcid":false,"given":"Sevgi Z.","family":"Gurbuz","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, University of Alabama, Tuscaloosa, AL, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0926-4120","authenticated-orcid":false,"given":"Moeness G.","family":"Amin","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, Villanova University, Villanova, PA, USA"}]}],"member":"263","reference":[{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2015.2452311"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpb.2012.02.003"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/APS.2008.4619934"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1249\/MSS.0b013e31825e1d31"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TAES.2016.140682"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/MAES.2015.7119820"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-11216-4_14"},{"key":"ref52","article-title":"Which training methods for GANs do actually Converge?","author":"mescheder","year":"0","journal-title":"Proc Int Conf Mach Learn (ICML)"},{"key":"ref11","first-page":"1","article-title":"Simulation of human microDopplers using computer animation data","author":"ram","year":"0","journal-title":"Proc IEEE Radar Conf"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1117\/12.2559155"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1117\/12.666163"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2003.819861"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/ICCWorkshops50388.2021.9473900"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TAES.2018.2883847"},{"key":"ref19","first-page":"197","article-title":"Unsupervised learning using generative adversarial networks on micro-Doppler spectrograms","author":"doherty","year":"0","journal-title":"Proc 16th Eur Radar Conf"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.4258\/hir.2019.25.4.344"},{"key":"ref51","article-title":"Kaggle: WGAN-gp in keras","year":"2019"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/DSC.2019.00061"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/TBME.2019.2893528"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1049\/iet-rsn.2015.0144"},{"key":"ref48","first-page":"80","article-title":"Computing the Fréchet distance between simple polygons in polynomial time","author":"buchin","year":"0","journal-title":"Proc 22nd Annu Symp Comput Geometry"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/RADAR.2017.7944316"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.3390\/rs14010123"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.3390\/rs11091068"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2907728"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/ICCWorkshops50388.2021.9473900"},{"key":"ref49","article-title":"Wiener adaptive filter for noise removal","year":"1995"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1049\/SBRA529E"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1201\/9781315155340"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1117\/12.666455"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/RADAR42522.2020.9114807"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/RADAR.2018.8378705"},{"key":"ref6","author":"chen","year":"2019","journal-title":"The Micro-Doppler Effect in Radar"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/JSEN.2020.3022376"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/JSEN.2022.3164152"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2003.813506"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.1998.710701"},{"key":"ref37","first-page":"5769","article-title":"Improved training of Wasserstein GANs","author":"gulrajani","year":"0","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1145\/3422622"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/RADAR42522.2020.9114646"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1016\/j.jcp.2019.109209"},{"key":"ref33","first-page":"214","article-title":"Wasserstein generative adversarial networks","volume":"70","author":"arjovsky","year":"0","journal-title":"Mach Learn Res"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/RadarConf2147009.2021.9455194"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3080655"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2018.2890128"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3068075"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.3390\/app10041449"},{"key":"ref24","first-page":"6572","article-title":"Neural ordinary differential equations","author":"chen","year":"0","journal-title":"Proc 32nd Int Conf Neural Inf Process Syst"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1038\/s42254-021-00314-5"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-021-26434-1"},{"key":"ref25","doi-asserted-by":"crossref","first-page":"686","DOI":"10.1016\/j.jcp.2018.10.045","article-title":"Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations","volume":"378","author":"raissi","year":"2019","journal-title":"J Comput Phys"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TAES.2020.2969579"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TAES.2021.3139848"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/RADAR.2019.8835589"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1016\/j.jcp.2019.05.027"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1007\/s41781-017-0004-6"},{"key":"ref29","doi-asserted-by":"crossref","first-page":"635","DOI":"10.4208\/cicp.OA-2020-0106","article-title":"Enforcing imprecise constraints on generative adversarial networks for emulating physical systems","volume":"30","author":"yang","year":"2021","journal-title":"Commun Comput Phys"}],"container-title":["IEEE Transactions on Aerospace and Electronic Systems"],"original-title":[],"link":[{"URL":"https:\/\/ieeexplore.ieee.org\/ielam\/7\/10146528\/9944857-aam.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/7\/10146528\/09944857.pdf?arnumber=9944857","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,6,26]],"date-time":"2023-06-26T18:54:12Z","timestamp":1687805652000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9944857\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,6]]},"references-count":57,"journal-issue":{"issue":"3"},"URL":"https:\/\/doi.org\/10.1109\/taes.2022.3221023","relation":{},"ISSN":["0018-9251","1557-9603","2371-9877"],"issn-type":[{"value":"0018-9251","type":"print"},{"value":"1557-9603","type":"electronic"},{"value":"2371-9877","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,6]]}}}