{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T20:13:58Z","timestamp":1777493638275,"version":"3.51.4"},"reference-count":29,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2017,7,9]],"date-time":"2017-07-09T00:00:00Z","timestamp":1499558400000},"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>To solve the unavailability of a traditional strapdown inertial navigation system (SINS) for unmanned underwater vehicles (UUVs) in the polar region, a polar grid navigation algorithm for UUVs is proposed in this paper. Precise navigation is the basis for UUVs to complete missions. The rapid convergence of Earth meridians and the serious polar environment make it difficult to establish the true heading of the UUV at a particular instant. Traditional SINS and traditional representation of position are not suitable in the polar region. Due to the restrictions of the complex underwater conditions in the polar region, a SINS based on the grid frame with the assistance of the OCTANS and the Doppler velocity log (DVL) is chosen for a UUV navigating in the polar region. Data fusion of the integrated navigation system is realized by a modified fuzzy adaptive Kalman filter (MFAKF). By neglecting the negative terms, and using T-S fuzzy logic in the adaptive regulation of the noise covariance, the proposed filter algorithm can improve navigation accuracy. Simulation and experimental results demonstrate that the polar grid navigation algorithm can effectively navigate a UUV sailing in the polar region.<\/jats:p>","DOI":"10.3390\/s17071599","type":"journal-article","created":{"date-parts":[[2017,7,10]],"date-time":"2017-07-10T11:05:31Z","timestamp":1499684731000},"page":"1599","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":33,"title":["Polar Grid Navigation Algorithm for Unmanned Underwater Vehicles"],"prefix":"10.3390","volume":"17","author":[{"given":"Zheping","family":"Yan","sequence":"first","affiliation":[{"name":"Marine Assembly and Automatic Technology Institute, College of Automation, Harbin Engineering University; Harbin 150001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lu","family":"Wang","sequence":"additional","affiliation":[{"name":"Marine Assembly and Automatic Technology Institute, College of Automation, Harbin Engineering University; Harbin 150001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wei","family":"Zhang","sequence":"additional","affiliation":[{"name":"Marine Assembly and Automatic Technology Institute, College of Automation, Harbin Engineering University; Harbin 150001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiajia","family":"Zhou","sequence":"additional","affiliation":[{"name":"Marine Assembly and Automatic Technology Institute, College of Automation, Harbin Engineering University; Harbin 150001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Man","family":"Wang","sequence":"additional","affiliation":[{"name":"Marine Assembly and Automatic Technology Institute, College of Automation, Harbin Engineering University; Harbin 150001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2017,7,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1016\/j.robot.2014.10.006","article-title":"Autonomous inspection of underwater structures","volume":"67","author":"Jacobi","year":"2015","journal-title":"Robot. 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