{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,17]],"date-time":"2026-03-17T18:36:21Z","timestamp":1773772581016,"version":"3.50.1"},"reference-count":30,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2013,1,15]],"date-time":"2013-01-15T00:00:00Z","timestamp":1358208000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>In-motion alignment of Strapdown Inertial Navigation Systems (SINS) without any geodetic-frame observations is one of the toughest challenges for Autonomous Underwater Vehicles (AUV). This paper presents a novel scheme for Doppler Velocity Log (DVL) aided SINS alignment using Unscented Kalman Filter (UKF) which allows large initial misalignments. With the proposed mechanism, a nonlinear SINS error model is presented and the measurement model is derived under the assumption that large misalignments may exist. Since a priori knowledge of the measurement noise covariance is of great importance to robustness of the UKF, the covariance-matching methods widely used in the Adaptive KF (AKF) are extended for use in Adaptive UKF (AUKF). Experimental results show that the proposed DVL-aided alignment model is effective with any initial heading errors. The performances of the adaptive filtering methods are evaluated with regards to their parameter estimation stability. Furthermore, it is clearly shown that the measurement noise covariance can be estimated reliably by the adaptive UKF methods and hence improve the performance of the alignment.<\/jats:p>","DOI":"10.3390\/s130101046","type":"journal-article","created":{"date-parts":[[2013,1,15]],"date-time":"2013-01-15T11:11:19Z","timestamp":1358248279000},"page":"1046-1063","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":81,"title":["A Novel Scheme for DVL-Aided SINS In-Motion Alignment Using UKF Techniques"],"prefix":"10.3390","volume":"13","author":[{"given":"Wanli","family":"Li","sequence":"first","affiliation":[{"name":"College of Mechatronics and Automation, National University of Defense Technology, Changsha 410073, China"},{"name":"School of Surveying and Geospatial Engineering, University of New South Wales, Sydney, NSW 2052, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jinling","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Surveying and Geospatial Engineering, University of New South Wales, Sydney, NSW 2052, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Liangqing","family":"Lu","sequence":"additional","affiliation":[{"name":"College of Mechatronics and Automation, National University of Defense Technology, Changsha 410073, China"},{"name":"School of Surveying and Geospatial Engineering, University of New South Wales, Sydney, NSW 2052, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenqi","family":"Wu","sequence":"additional","affiliation":[{"name":"College of Mechatronics and Automation, National University of Defense Technology, Changsha 410073, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2013,1,15]]},"reference":[{"key":"ref_1","unstructured":"Kinsey, J.C., Eustice, R., and Whitcomb, L.L. (, January September). A Survey of Underwater Vehicle Navigation: Recent Advances and New Challenges. Lisbon, Portugal."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"581","DOI":"10.1109\/TSMCC.2008.919147","article-title":"Navigation technologies for autonomous underwater vehicles","volume":"38","author":"Stutters","year":"2008","journal-title":"IEEE Trans. Syst. Man Cy. C"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Li, W., Wang, J., Wu, W., and Lu, L. (2012). A fast SINS initial alignment scheme for underwater vehicle applications. J. Navig.","DOI":"10.1017\/S0373463312000318"},{"key":"ref_4","first-page":"581","article-title":"Coarse alignment of a ship's strapdown inertial attitude reference system using velocity loci","volume":"38","author":"Silson","year":"2011","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Gao, W., Zhang, X., Zhao, G., and Ben, Y. (2010, January 20\u201323). A Fine Alignment Method about Doppler-assisted SINS. Harbin, China.","DOI":"10.1109\/ICINFA.2010.5512429"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Ben, Y., Zhu, Z., Li, Q., and Wu, X. (2011, January 7\u201310). DVL Aided Fine Alignment for Marine SINS. Beijing, China.","DOI":"10.1109\/ICMA.2011.5985958"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"929","DOI":"10.1007\/s11431-010-0119-z","article-title":"Unscented Kalman filtering in the additive noise case","volume":"53","author":"Liu","year":"2010","journal-title":"Sci. China Technol. Sc."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"776","DOI":"10.1007\/s12555-010-0409-z","article-title":"Non-symmetric unscented transformation with application to in-flight alignment","volume":"8","author":"Kwangjin","year":"2010","journal-title":"Int. J. Control. Autom. Syst."},{"key":"ref_9","unstructured":"Wang, Q., Li, Y., Rizos, C., and Li, S. The UKF and CDKF for Low-Cost SDINS\/GPS in-Motion Alignment. Yokohama, Japan."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Seo, W., Hwang, S., Park, J., and Lee, J. (2012). Precise outdoor localization with a GPS\u2013INS integration system. Robotica.","DOI":"10.1017\/S0263574712000379"},{"key":"ref_11","unstructured":"Shin, E. (2005). Estimation Techniques for Low-Cost Inertial Navigation. [Ph.D. Thesis, Department of Geomatics Engineering, University of Calgary]."},{"key":"ref_12","unstructured":"Petovello, M.G., Cannon, M.E., and Lachapelle, G. (2003, January 28\u201330). Kalman Filter Reliability Analysis Using Different Update Strategies. Montreal, QC, Canada."},{"key":"ref_13","unstructured":"Shin, E. (2001). Accuracy Improvement of Low Cost INS\/GPS for Land Application. [M.Sc. Thesis, Department of Geomatics Engineering, University of Calgary]."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"5134","DOI":"10.3390\/s120405134","article-title":"Benefits of combined GPS\/GLONASS with low-cost MEMS IMUs for vehicular urban navigation","volume":"12","author":"Angrisano","year":"2012","journal-title":"Sensors"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Zhang, S. (2009, January 19\u201320). An Adaptive Unscented Kalman filter for Dead Reckoning Systems. Beijing, China.","DOI":"10.1109\/ICIECS.2009.5365064"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"517","DOI":"10.1017\/S0373463307004316","article-title":"Improving adaptive Kalman estimation in GPS\/INS integration","volume":"60","author":"Ding","year":"2007","journal-title":"J. Navig."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1504\/IJCAT.2011.042240","article-title":"SINS\/CNS integrated navigation solution using adaptive unscented Kalman filtering","volume":"41","author":"Qu","year":"2011","journal-title":"Int. J. Comput. Appl. Technol."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"297","DOI":"10.1002\/j.2161-4296.1999.tb02416.x","article-title":"Stochastic modeling for RTK GPS\/Glonass positioning","volume":"46","author":"Wang","year":"2000","journal-title":"J. Inst. Navig."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1378","DOI":"10.1109\/TIM.2010.2084710","article-title":"Study on innovation adaptive EKF for in-flight Alignment of airborne POS","volume":"60","author":"Fang","year":"2011","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref_20","unstructured":"Kong, X., Nebot, E.M., and Durrant-Whyte, H. (, January May). Development of a Non-Linear Psi-Angle Model for Large Misalignment Errors and its Application in INS Alignment and Calibration. Detroit, MI, USA."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"124","DOI":"10.1109\/TRO.2006.886829","article-title":"Adaptive identification on the group of rigid-body rotations and its application to underwater vehicle navigation","volume":"23","author":"Kinsey","year":"2007","journal-title":"IEEE Trans. Robot."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"663","DOI":"10.1017\/S0373463310000214","article-title":"A novel initial alignment scheme for low-cost INS aided by GPS for land vehicle application","volume":"63","author":"Han","year":"2010","journal-title":"J. Navig."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1016\/j.automatica.2005.10.004","article-title":"Performance evaluation of UKF-based nonlinear filtering","volume":"42","author":"Xiong","year":"2006","journal-title":"Automatica."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"357","DOI":"10.1109\/LSP.2005.845592","article-title":"Unscented Kalman filtering for additive noise case: augmented versus non-augmented","volume":"12","author":"Wu","year":"2005","journal-title":"IEEE. Signal Proc. Lett."},{"key":"ref_25","unstructured":"Van, R. (2004). Sigma-Point Kalman Filters for Probabilistic Inference in Dynamic State-Space Models. [Ph.D. Thesis, Oregon Health & Science University]."},{"key":"ref_26","first-page":"253","article-title":"Application of simplified UKF in SINS initial alignment for large misalignment angles","volume":"16","author":"Yan","year":"2008","journal-title":"J. Chin. Inert. Technol."},{"key":"ref_27","unstructured":"Xu, J., Jing, Y., Dimirovski, G., and Ban, Y. (2008, January 11\u201313). Two-Stage Unscented Kalman Filter for Nonlinear Systems in the Presence of Unknown Random Bias. Seattle, Washington USA."},{"key":"ref_28","unstructured":"Wan, E.A., and Van, R. (2000, January 1\u20134). The Unscented Kalman Filter for Nonlinear Estimation. Lake Louise, AB, Canada."},{"key":"ref_29","first-page":"33","article-title":"Evaluating the performance of adaptive Kalman filter methods in GPS\/INS integration","volume":"9","author":"Almagbile","year":"2010","journal-title":"CPGPS"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1007\/s00190-006-0041-0","article-title":"An optimal adaptive Kalman filter","volume":"80","author":"Yang","year":"2006","journal-title":"J. Geodesy."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/13\/1\/1046\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T21:44:19Z","timestamp":1760219059000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/13\/1\/1046"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2013,1,15]]},"references-count":30,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2013,1]]}},"alternative-id":["s130101046"],"URL":"https:\/\/doi.org\/10.3390\/s130101046","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2013,1,15]]}}}