{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T16:22:34Z","timestamp":1783614154589,"version":"3.55.0"},"reference-count":36,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2020,8,28]],"date-time":"2020-08-28T00:00:00Z","timestamp":1598572800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The purpose of this paper is to investigate the possibility of developing and using an intelligent, flexible, and reliable acoustic system, designed to discover, locate, and transmit the position of unmanned aerial vehicles (UAVs). Such an application is very useful for monitoring sensitive areas and land territories subject to privacy. The software functional components of the proposed detection and location algorithm were developed employing acoustic signal analysis and concurrent neural networks (CoNNs). An analysis of the detection and tracking performance for remotely piloted aircraft systems (RPASs), measured with a dedicated spiral microphone array with MEMS microphones, was also performed. The detection and tracking algorithms were implemented based on spectrograms decomposition and adaptive filters. In this research, spectrograms with Cohen class decomposition, log-Mel spectrograms, harmonic-percussive source separation and raw audio waveforms of the audio sample, collected from the spiral microphone array\u2014as an input to the Concurrent Neural Networks were used, in order to determine and classify the number of detected drones in the perimeter of interest.<\/jats:p>","DOI":"10.3390\/s20174870","type":"journal-article","created":{"date-parts":[[2020,8,28]],"date-time":"2020-08-28T09:17:08Z","timestamp":1598606228000},"page":"4870","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":78,"title":["Development of an Acoustic System for UAV Detection"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3882-5062","authenticated-orcid":false,"given":"C\u0103t\u0103lin","family":"Dumitrescu","sequence":"first","affiliation":[{"name":"Department Telematics and Electronics for Transports, University \u201cPolitehnica\u201d of Bucharest, 060042 Bucharest, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9247-2264","authenticated-orcid":false,"given":"Marius","family":"Minea","sequence":"additional","affiliation":[{"name":"Department Telematics and Electronics for Transports, University \u201cPolitehnica\u201d of Bucharest, 060042 Bucharest, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ilona M\u0103d\u0103lina","family":"Costea","sequence":"additional","affiliation":[{"name":"Department Telematics and Electronics for Transports, University \u201cPolitehnica\u201d of Bucharest, 060042 Bucharest, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ionut","family":"Cosmin Chiva","sequence":"additional","affiliation":[{"name":"Department Telematics and Electronics for Transports, University \u201cPolitehnica\u201d of Bucharest, 060042 Bucharest, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Augustin","family":"Semenescu","sequence":"additional","affiliation":[{"name":"Department Engineering and Management for Transports, University \u201cPolitehnica\u201d of Bucharest, 060042 Bucharest, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,8,28]]},"reference":[{"key":"ref_1","unstructured":"(2020, May 20). 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