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China","award":["61906145"],"award-info":[{"award-number":["61906145"]}]},{"name":"Science and Technology Innovation Team in Shaanxi Province of China","award":["2020TD-017"],"award-info":[{"award-number":["2020TD-017"]}]},{"name":"Science and Technology Innovation Team in Shaanxi Province of China","award":["2020CFA001"],"award-info":[{"award-number":["2020CFA001"]}]},{"name":"Foundation of Intelligent Decision and Cognitive Innovation Center of State Administration of Science, Technology and Industry for National Defense, China","award":["U22B2018"],"award-info":[{"award-number":["U22B2018"]}]},{"name":"Foundation of Intelligent Decision and Cognitive Innovation Center of State Administration of Science, Technology and Industry for National Defense, China","award":["61771376"],"award-info":[{"award-number":["61771376"]}]},{"name":"Foundation of Intelligent Decision and Cognitive Innovation Center of State Administration of Science, Technology and Industry for National Defense, China","award":["61771380"],"award-info":[{"award-number":["61771380"]}]},{"name":"Foundation of Intelligent Decision and Cognitive Innovation Center of State Administration of Science, Technology and Industry for National Defense, China","award":["61836009"],"award-info":[{"award-number":["61836009"]}]},{"name":"Foundation of Intelligent Decision and Cognitive Innovation Center of State Administration of Science, Technology and Industry for National Defense, China","award":["61906145"],"award-info":[{"award-number":["61906145"]}]},{"name":"Foundation of Intelligent Decision and Cognitive Innovation Center of State Administration of Science, Technology and Industry for National Defense, China","award":["2020TD-017"],"award-info":[{"award-number":["2020TD-017"]}]},{"name":"Foundation of Intelligent Decision and Cognitive Innovation Center of State Administration of Science, Technology and Industry for National Defense, China","award":["2020CFA001"],"award-info":[{"award-number":["2020CFA001"]}]},{"name":"Key Project of Hubei Provincial Natural Science Foundation","award":["U22B2018"],"award-info":[{"award-number":["U22B2018"]}]},{"name":"Key Project of Hubei Provincial Natural Science Foundation","award":["61771376"],"award-info":[{"award-number":["61771376"]}]},{"name":"Key Project of Hubei Provincial Natural Science Foundation","award":["61771380"],"award-info":[{"award-number":["61771380"]}]},{"name":"Key Project of Hubei Provincial Natural Science Foundation","award":["61836009"],"award-info":[{"award-number":["61836009"]}]},{"name":"Key Project of Hubei Provincial Natural Science Foundation","award":["61906145"],"award-info":[{"award-number":["61906145"]}]},{"name":"Key Project of Hubei Provincial Natural Science Foundation","award":["2020TD-017"],"award-info":[{"award-number":["2020TD-017"]}]},{"name":"Key Project of Hubei Provincial Natural Science Foundation","award":["2020CFA001"],"award-info":[{"award-number":["2020CFA001"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Radar emitter identification (REI) aims to extract the fingerprint of an emitter and determine the individual to which it belongs. Although many methods have used deep neural networks (DNNs) for an end-to-end REI, most of them only focus on a single view of signals, such as spectrogram, bi-spectrum, signal waveforms, and so on. When the electromagnetic environment varies, the performance of DNN will be significantly degraded. In this paper, a multi-view adaptive fusion network (MAFN) is proposed by simultaneously exploring the signal waveform and ambiguity function (AF). First, the original waveform and ambiguity function of the radar signals are used separately for feature extraction. Then, a multi-scale feature-level fusion module is constructed for the fusion of multi-view features from waveforms and AF, via the Atrous Spatial Pyramid Pooling (ASPP) structure. Next, the class probability is modeled as Dirichlet distribution to perform adaptive decision-level fusion via evidence theory. Extensive experiments are conducted on two datasets, and the results show that the proposed MAFN can achieve accurate classification of radar emitters and is more robust than its counterparts.<\/jats:p>","DOI":"10.3390\/rs15071762","type":"journal-article","created":{"date-parts":[[2023,3,27]],"date-time":"2023-03-27T02:18:27Z","timestamp":1679883507000},"page":"1762","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Radar Emitter Identification with Multi-View Adaptive Fusion Network (MAFN)"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4796-5737","authenticated-orcid":false,"given":"Shuyuan","family":"Yang","sequence":"first","affiliation":[{"name":"School of Artificial Intelligence, Xidian University, Xi\u2019an 710071, China"},{"name":"Intelligent Decision and Cognitive Innovation Center of State Administration of Science, Technology and Industry for National Defense, Beijing 100048, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1349-3724","authenticated-orcid":false,"given":"Tongqing","family":"Peng","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, Xidian University, Xi\u2019an 710071, China"}]},{"given":"Huiling","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, Xidian University, Xi\u2019an 710071, China"}]},{"given":"Chen","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, Xidian University, Xi\u2019an 710071, China"},{"name":"Intelligent Decision and Cognitive Innovation Center of State Administration of Science, Technology and Industry for National Defense, Beijing 100048, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7372-9180","authenticated-orcid":false,"given":"Zhixi","family":"Feng","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, Xidian University, Xi\u2019an 710071, China"},{"name":"Intelligent Decision and Cognitive Innovation Center of State Administration of Science, Technology and Industry for National Defense, Beijing 100048, China"}]},{"given":"Min","family":"Wang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Radar Signal Processing, Xidian University, Xi\u2019an, 710071, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,3,24]]},"reference":[{"key":"ref_1","first-page":"8","article-title":"Signal Recognition in a Complex Radar Environment","volume":"3","author":"Saperstein","year":"1977","journal-title":"Electronic"},{"key":"ref_2","unstructured":"Kawalec, A., and Owczarek, R. 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