{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,25]],"date-time":"2026-06-25T15:47:49Z","timestamp":1782402469994,"version":"3.54.5"},"reference-count":36,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2023,1,18]],"date-time":"2023-01-18T00:00:00Z","timestamp":1674000000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["62131020"],"award-info":[{"award-number":["62131020"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Micro-motion jamming is a new jamming method to inverse synthetic aperture radar (ISAR) in recent years. Compared with traditional jamming methods, it is more flexible and controllable, and is a great threat to ISAR. The prerequisite of taking relevant anti-jamming measures is to recognize the patterns of micro-motion jamming. In this paper, a method of micro-motion jamming pattern recognition based on complex-valued convolutional neural network (CV-CNN) is proposed. The micro-motion jamming echo signals are serialized and input to the network, and the result of recognition is output. Compared with real-valued convolutional neural network (RV-CNN), it can be found that the proposed method has a higher recognition accuracy rate. Additionally, the recognition accuracy rate is analyzed with different signal-to-noise ratio (SNR) and number of training samples. Simulation results prove the effectiveness of the proposed recognition method.<\/jats:p>","DOI":"10.3390\/s23031118","type":"journal-article","created":{"date-parts":[[2023,1,19]],"date-time":"2023-01-19T01:33:51Z","timestamp":1674092031000},"page":"1118","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Recognition of Micro-Motion Jamming Based on Complex-Valued Convolutional Neural Network"],"prefix":"10.3390","volume":"23","author":[{"given":"Chongwei","family":"Shi","sequence":"first","affiliation":[{"name":"Information and Navigation School, Air Force Engineering University, Xi\u2019an 710077, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qun","family":"Zhang","sequence":"additional","affiliation":[{"name":"Information and Navigation School, Air Force Engineering University, Xi\u2019an 710077, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tao","family":"Lin","sequence":"additional","affiliation":[{"name":"Information and Navigation School, Air Force Engineering University, Xi\u2019an 710077, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0453-2621","authenticated-orcid":false,"given":"Zhidong","family":"Liu","sequence":"additional","affiliation":[{"name":"Information and Navigation School, Air Force Engineering University, Xi\u2019an 710077, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shiliang","family":"Li","sequence":"additional","affiliation":[{"name":"Equipment Management and Unmanned Aerial Vehicle Engineering School, Air Force Engineering University, Xi\u2019an 710051, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,1,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"633","DOI":"10.1109\/22.989948","article-title":"Electronic warfare systems","volume":"50","author":"Spezio","year":"2002","journal-title":"IEEE Trans. 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