{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T07:26:35Z","timestamp":1774509995329,"version":"3.50.1"},"reference-count":46,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2026,3,23]],"date-time":"2026-03-23T00:00:00Z","timestamp":1774224000000},"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>In the state estimation problem for nonlinear systems, the Unscented Kalman Filter (UKF) has gained attention as an algorithm capable of accurate state estimation based on high-fidelity discretization for strongly nonlinear systems. Furthermore, for applying the UKF to continuous-time state\u2013space models, a method employing the Runge\u2013Kutta method in the time-update equation for sigma points has already been proposed to achieve high-precision state estimation. While this method uses high-order numerical approximations, the associated decrease in computational efficiency due to processing time becomes problematic. It is thus unsuitable for the state estimation of relatively fast-moving objects, such as autonomous vehicles and drones, which require high sampling frequencies. In this study, to reduce computational load while achieving relatively high estimation accuracy, we newly apply the Adams\u2013Bashforth method to the UKF algorithm. The effectiveness of the proposed method is demonstrated by first explaining a low-dimensional model\u2019s state estimation problem, followed by a comparison of estimation accuracy and computation time in state estimation simulations for the UAV model of an Osprey-type drone.<\/jats:p>","DOI":"10.3390\/s26062009","type":"journal-article","created":{"date-parts":[[2026,3,23]],"date-time":"2026-03-23T15:54:53Z","timestamp":1774281293000},"page":"2009","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["An Unscented Kalman Filter Based on the Adams\u2013Bashforth Method with Applications to the State Estimation of Osprey-Type Drones Composed of Tiltable Rotor Mechanisms"],"prefix":"10.3390","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5250-2211","authenticated-orcid":false,"given":"Keigo","family":"Watanabe","sequence":"first","affiliation":[{"name":"Graduate School of Environmental, Life, Natural Science and Technology, Okayama University, Okayama 700-8530, Japan"},{"name":"Faculty of International Economics and Management, International Pacific University (IPU), Tokyo Campus, Chiba 272-001, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Soma","family":"Takeda","sequence":"additional","affiliation":[{"name":"Sony Group Corporation, Tokyo 108-0075, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Isaku","family":"Nagai","sequence":"additional","affiliation":[{"name":"National Institute of Technology, Mitsue College, Matsue 690-0865, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2026,3,23]]},"reference":[{"key":"ref_1","unstructured":"Bar-Shalom, Y., Li, X.R., and Kirubarajan, T. 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