{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,22]],"date-time":"2026-03-22T06:50:17Z","timestamp":1774162217694,"version":"3.50.1"},"reference-count":49,"publisher":"Wiley","issue":"11","license":[{"start":{"date-parts":[[2023,9,1]],"date-time":"2023-09-01T00:00:00Z","timestamp":1693526400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61876189"],"award-info":[{"award-number":["61876189"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61273275"],"award-info":[{"award-number":["61273275"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61703426"],"award-info":[{"award-number":["61703426"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["advanced.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Advanced Intelligent Systems"],"published-print":{"date-parts":[[2023,11]]},"abstract":"<jats:p>Radar high\u2010resolution range profile (HRRP) is widely used in radar automatic target recognition due to its advantages such as easy availability, convenient processing, and small storage space. Current recognition methods for HRRP sequences mainly focus on the temporal information of HRRP sequences, which cannot fully utilize the temporal and spatial information contained in HRRP sequences. Moreover, most of these methods fail in long\u2010range modeling and global information extraction of HRRP sequences. To solve above problems, a HRRP sequence recognition method based on transformer with temporal\u2013spatial fusion and label smoothing (TSF\u2013transformer\u2013LS) is proposed. TSF\u2013transformer\u2013LS contains temporal transformer blocks and spatial transformer blocks, which are used to extract deep global features of HRRP sequences in the time domain and space domain, respectively. Then, an attention fusion mechanism is developed to realize the adaptive fusion of temporal and spatial features. Moreover, label smoothing is used to add noise to sample labels, which can solve the overfitting problem of transformer caused by a large amount of noise hidden in HRRP in real scenes. Experiments on MSTAR, a standard dataset, show that the proposed method outperforms other methods in recognition performance. Furthermore, the effectiveness and interpretability of the method are explored.<\/jats:p>","DOI":"10.1002\/aisy.202300286","type":"journal-article","created":{"date-parts":[[2023,9,1]],"date-time":"2023-09-01T09:55:03Z","timestamp":1693562103000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["High\u2010Resolution Range Profile Sequence Recognition Based on Transformer with Temporal\u2013Spatial Fusion and Label Smoothing"],"prefix":"10.1002","volume":"5","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2785-9539","authenticated-orcid":false,"given":"Xiaodan","family":"Wang","sequence":"first","affiliation":[{"name":"College of Air and Missile Defense Air Force Engineering University  Xi'an 710051 China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Peng","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Air and Missile Defense Air Force Engineering University  Xi'an 710051 China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yafei","family":"Song","sequence":"additional","affiliation":[{"name":"College of Air and Missile Defense Air Force Engineering University  Xi'an 710051 China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6810-8446","authenticated-orcid":false,"given":"Qian","family":"Xiang","sequence":"additional","affiliation":[{"name":"College of Air and Missile Defense Air Force Engineering University  Xi'an 710051 China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jingtai","family":"Li","sequence":"additional","affiliation":[{"name":"College of Air and Missile Defense Air Force Engineering University  Xi'an 710051 China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2023,9]]},"reference":[{"key":"e_1_2_9_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/MAES.2021.3049857"},{"key":"e_1_2_9_3_1","doi-asserted-by":"publisher","DOI":"10.1088\/1742-6596\/1651\/1\/012153"},{"key":"e_1_2_9_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/TAES.2019.2905281"},{"key":"e_1_2_9_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2020.08.050"},{"key":"e_1_2_9_6_1","doi-asserted-by":"publisher","DOI":"10.1002\/int.22302"},{"key":"e_1_2_9_7_1","doi-asserted-by":"publisher","DOI":"10.3390\/rs13071259"},{"key":"e_1_2_9_8_1","first-page":"4026005","volume":"19","author":"Zeng Z.","year":"2022","journal-title":"IEEE Geosci. Remote Sens."},{"key":"e_1_2_9_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/TAES.2021.3116120"},{"key":"e_1_2_9_10_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.sigpro.2021.108010"},{"key":"e_1_2_9_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2020.3027470"},{"key":"e_1_2_9_12_1","first-page":"117","volume-title":"Automatic Target Recognition XXXII","author":"Jouny I.","year":"2022"},{"key":"e_1_2_9_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3056671"},{"key":"e_1_2_9_14_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.dsp.2021.103212"},{"key":"e_1_2_9_15_1","doi-asserted-by":"crossref","unstructured":"Q.Liu X.Zhang Y.Liu in2022 7th Int. Conf. Signal and Image Processing (ICSIP) IEEE Suzhou China2022 pp.167\u2013171.","DOI":"10.1109\/ICSIP55141.2022.9886234"},{"key":"e_1_2_9_16_1","first-page":"5100814","volume":"60","author":"Pan M.","year":"2022","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"e_1_2_9_17_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10462-021-09958-2"},{"key":"e_1_2_9_18_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2021.103982"},{"key":"e_1_2_9_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3077350"},{"key":"e_1_2_9_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/LWC.2021.3132067"},{"key":"e_1_2_9_21_1","doi-asserted-by":"crossref","unstructured":"A.Arnab M.Dehghani G.Heigold C.Sun M.Lu\u010di\u0107 C.Schmid in2021 IEEE\/CVF Int. Conf. Computer Vision (ICCV) IEEE Montreal QC Canada2021 pp.6816\u20136826.","DOI":"10.1109\/ICCV48922.2021.00676"},{"key":"e_1_2_9_22_1","doi-asserted-by":"crossref","unstructured":"Z.Chen L.Xie J.Niu X.Liu L.Wei Q.Tian in2021 IEEE\/CVF Int. Conf. Computer Vision (ICCV) IEEE Montreal QC Canada2021 pp.569\u2013578.","DOI":"10.1109\/ICCV48922.2021.00063"},{"key":"e_1_2_9_23_1","first-page":"87","volume":"1","author":"Han K.","year":"2022","journal-title":"IEEE Trans. Pattern Anal."},{"key":"e_1_2_9_24_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2021.3076835"},{"key":"e_1_2_9_25_1","unstructured":"K.Chen G.Chen D.Xu L.Zhang Y.Huang A.Knoll https:\/\/ui.adsabs.harvard.edu\/abs\/2021arXiv210205624C(accessed: May 2021)."},{"key":"e_1_2_9_26_1","unstructured":"M.Liu S.Ren S.Ma J.Jiao Y.Chen Z.Wang W.Song https:\/\/ui.adsabs.harvard.edu\/abs\/2021arXiv210314438L(accessed: March 2021)."},{"key":"e_1_2_9_27_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.enbuild.2021.111608"},{"key":"e_1_2_9_28_1","doi-asserted-by":"publisher","DOI":"10.1109\/78.942617"},{"key":"e_1_2_9_29_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2006.873534"},{"key":"e_1_2_9_30_1","doi-asserted-by":"publisher","DOI":"10.1109\/TAES.2014.120266"},{"key":"e_1_2_9_31_1","doi-asserted-by":"crossref","first-page":"302","DOI":"10.1117\/12.541454","volume-title":"Algorithms for Synthetic Aperture Radar Imagery XI","author":"Albrecht T. W.","year":"2004"},{"key":"e_1_2_9_32_1","first-page":"861","volume":"28","author":"Lei L.","year":"2013","journal-title":"J. Control Decis."},{"key":"e_1_2_9_33_1","first-page":"657","volume":"7","author":"Li R.","year":"2019","journal-title":"IEEE Access"},{"key":"e_1_2_9_34_1","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2021.3052536"},{"key":"e_1_2_9_35_1","first-page":"174","volume":"53","author":"Zhang Z.","year":"2023","journal-title":"IEEE Trans. Syst. Man Cybern.: Syst."},{"key":"e_1_2_9_36_1","first-page":"2775","volume":"43","author":"Zhang Y.","year":"2021","journal-title":"J. Syst. Eng. Electron."},{"key":"e_1_2_9_37_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10044-023-01150-2"},{"key":"e_1_2_9_38_1","first-page":"201","volume":"32","author":"Liu Z.","year":"2021","journal-title":"IEEE Trans. Neural Networks Learn."},{"key":"e_1_2_9_39_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.2969450"},{"key":"e_1_2_9_40_1","first-page":"873","volume":"18","author":"Feng J.","year":"2022","journal-title":"IEEE Trans. Ind. Inf."},{"key":"e_1_2_9_41_1","unstructured":"M.Xu W.Dai C.Liu X.Gao W.Lin G.Qi H.Xiong https:\/\/ui.adsabs.harvard.edu\/abs\/2020arXiv200102908X(accessed: March 2021)."},{"key":"e_1_2_9_42_1","first-page":"5410618","volume":"60","author":"Chen G.","year":"2022","journal-title":"IEEE Trans. Geosci. Remote"},{"key":"e_1_2_9_43_1","doi-asserted-by":"publisher","DOI":"10.1186\/s13634-022-00909-9"},{"key":"e_1_2_9_44_1","unstructured":"R.M\u00fcller S.Kornblith G.Hinton inProc. 33rd Int. Conf. Neural Information Processing Systems (NeurIPS) MIT Press Vancouver Canada2019 pp.4694\u20134703."},{"key":"e_1_2_9_45_1","doi-asserted-by":"publisher","DOI":"10.3390\/s18051585"},{"key":"e_1_2_9_46_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2019.04.014"},{"key":"e_1_2_9_47_1","first-page":"654","volume":"10","author":"Elsayed N.","year":"2019","journal-title":"Int. J. Adv. Comput. Sci."},{"key":"e_1_2_9_48_1","unstructured":"S.Bai J.Zico Kolter V.Koltun https:\/\/ui.adsabs.harvard.edu\/abs\/2018arXiv180301271B(accessed: April 2018)."},{"key":"e_1_2_9_49_1","unstructured":"H.Liu Z.Dai D. R.So Q. V.Le https:\/\/ui.adsabs.harvard.edu\/abs\/2021arXiv210508050L(accessed: June 2021)."},{"key":"e_1_2_9_50_1","unstructured":"K.Fauvel T.Lin V.Masson \u00c9.Fromont A.Termier https:\/\/ui.adsabs.harvard.edu\/abs\/2020arXiv200904796F(accessed: December 2021)."}],"container-title":["Advanced Intelligent Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/advanced.onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/aisy.202300286","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,7]],"date-time":"2025-10-07T18:31:54Z","timestamp":1759861914000},"score":1,"resource":{"primary":{"URL":"https:\/\/advanced.onlinelibrary.wiley.com\/doi\/10.1002\/aisy.202300286"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,9]]},"references-count":49,"journal-issue":{"issue":"11","published-print":{"date-parts":[[2023,11]]}},"alternative-id":["10.1002\/aisy.202300286"],"URL":"https:\/\/doi.org\/10.1002\/aisy.202300286","archive":["Portico"],"relation":{},"ISSN":["2640-4567","2640-4567"],"issn-type":[{"value":"2640-4567","type":"print"},{"value":"2640-4567","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,9]]},"assertion":[{"value":"2023-05-29","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2023-09-01","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"2300286"}}