{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,30]],"date-time":"2026-01-30T17:48:38Z","timestamp":1769795318494,"version":"3.49.0"},"reference-count":61,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2026,1,23]],"date-time":"2026-01-23T00:00:00Z","timestamp":1769126400000},"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>Unmanned aerial vehicles (UAVs) increasingly share low-altitude airspace with birds, making early distinguishing between drones and biological targets critical for safety and security. This work addresses long-range scenarios where objects occupy only a few pixels and appearance-based recognition becomes unreliable. We develop a model-driven simulation pipeline that generates synthetic data with a controlled camera model, atmospheric background and realistic motion of three aerial target types: multicopter, fixed-wing UAV and bird. From these sequences, each track is encoded as a time series of image-plane coordinates and apparent size, and a bidirectional long short-term memory (LSTM) network is trained to classify trajectories as drone-like or bird-like. The model learns characteristic differences in smoothness, turning behavior and velocity fluctuations, and to achieve reliable separation between drone and bird motion patterns on synthetic test data. Motion-trajectory cues alone can support early distinguishing of drones from birds when visual details are scarce, providing a complementary signal to conventional image-based detection. The proposed synthetic data and sequence classification pipeline forms a reproducible testbed that can be extended with real trajectories from radar or video tracking systems and used to prototype and benchmark trajectory-based recognizers for integrated surveillance solutions. The proposed method is designed to generalize naturally to real surveillance systems, as it relies on trajectory-level motion patterns rather than appearance-based features that are sensitive to sensor quality, illumination, or weather conditions.<\/jats:p>","DOI":"10.3390\/s26030755","type":"journal-article","created":{"date-parts":[[2026,1,26]],"date-time":"2026-01-26T16:13:48Z","timestamp":1769444028000},"page":"755","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Distinguishing a Drone from Birds Based on Trajectory Movement and Deep Learning"],"prefix":"10.3390","volume":"26","author":[{"given":"Andrii","family":"Nesteruk","sequence":"first","affiliation":[{"name":"Faculty of Informatics and Computer Engineering, National Technical University of Ukraine \u201cIgor Sikorsky Kyiv Polytechnic Institute\u201d, 37 Peremohy Ave., 03056 Kyiv, Ukraine"},{"name":"Faculty of Electrical and Computer Engineering, Cracow University of Technology, Warszawska 24, 31-155 Cracow, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Valerii","family":"Nikitin","sequence":"additional","affiliation":[{"name":"Faculty of Informatics and Computer Engineering, National Technical University of Ukraine \u201cIgor Sikorsky Kyiv Polytechnic Institute\u201d, 37 Peremohy Ave., 03056 Kyiv, Ukraine"},{"name":"Faculty of Electrical and Computer Engineering, Cracow University of Technology, Warszawska 24, 31-155 Cracow, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yosyp","family":"Albrekht","sequence":"additional","affiliation":[{"name":"Faculty of Informatics and Computer Engineering, National Technical University of Ukraine \u201cIgor Sikorsky Kyiv Polytechnic Institute\u201d, 37 Peremohy Ave., 03056 Kyiv, Ukraine"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7365-8888","authenticated-orcid":false,"given":"\u0141ukasz","family":"\u015acis\u0142o","sequence":"additional","affiliation":[{"name":"Faculty of Electrical and Computer Engineering, Cracow University of Technology, Warszawska 24, 31-155 Cracow, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7853-5214","authenticated-orcid":false,"given":"Damian","family":"Grela","sequence":"additional","affiliation":[{"name":"Faculty of Electrical and Computer Engineering, Cracow University of Technology, Warszawska 24, 31-155 Cracow, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9874-7070","authenticated-orcid":false,"given":"Pawe\u0142","family":"Kr\u00f3l","sequence":"additional","affiliation":[{"name":"Faculty of Electrical and Computer Engineering, Cracow University of Technology, Warszawska 24, 31-155 Cracow, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2026,1,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Melnychenko, O., Scislo, L., Savenko, O., Sachenko, A., and Radiuk, P. 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