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In this work, a deep learning-based framework named SigdetNet is proposed, which takes the power spectrum as the network\u2019s input to localize the spectral locations of the signals. In the proposed framework, Welch\u2019s periodogram is applied to reduce the variance in the power spectral density (PSD), followed by logarithmic transformation for signal enhancement. In particular, an encoder-decoder network with the embedding pyramid pooling module is constructed, aiming to extract multi-scale features relevant to signal detection. The influence of the frequency resolution, network architecture, and loss function on the detection performance is investigated. Extensive simulations are carried out to demonstrate that the proposed multi-signal detection method can achieve better performance than the other benchmark schemes.<\/jats:p>","DOI":"10.3390\/s22103909","type":"journal-article","created":{"date-parts":[[2022,5,21]],"date-time":"2022-05-21T09:18:08Z","timestamp":1653124688000},"page":"3909","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":24,"title":["Multi-Signal Detection Framework: A Deep Learning Based Carrier Frequency and Bandwidth Estimation"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5115-825X","authenticated-orcid":false,"given":"Meiyan","family":"Lin","sequence":"first","affiliation":[{"name":"National Space Science Center, Chinese Academy of Sciences, Beijing 100190, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100190, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8758-9804","authenticated-orcid":false,"given":"Xiaoxu","family":"Zhang","sequence":"additional","affiliation":[{"name":"National Space Science Center, Chinese Academy of Sciences, Beijing 100190, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100190, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0252-230X","authenticated-orcid":false,"given":"Ye","family":"Tian","sequence":"additional","affiliation":[{"name":"National Space Science Center, Chinese Academy of Sciences, Beijing 100190, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100190, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9745-4177","authenticated-orcid":false,"given":"Yonghui","family":"Huang","sequence":"additional","affiliation":[{"name":"National Space Science Center, Chinese Academy of Sciences, Beijing 100190, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,5,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1109\/MCOMSTD.2018.1700054","article-title":"IEEE 1900.5.2: Standard Method for Modeling Spectrum Consumption: Introduction and Use Cases","volume":"2","author":"Bastidas","year":"2018","journal-title":"IEEE Commun. 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