{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T03:48:08Z","timestamp":1760240888299,"version":"build-2065373602"},"reference-count":30,"publisher":"MDPI AG","issue":"20","license":[{"start":{"date-parts":[[2019,10,17]],"date-time":"2019-10-17T00:00:00Z","timestamp":1571270400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the Fundamental Research Funds for the Central Universities","award":["3072019CF0405","3072019CFM0402"],"award-info":[{"award-number":["3072019CF0405","3072019CFM0402"]}]},{"name":"the National Natural Science Foundation of China (NSFC)","award":["61803118"],"award-info":[{"award-number":["61803118"]}]},{"name":"the Science and Technology Research Program of Chongqing Municipal Education Commission","award":["KJZD-K201804701"],"award-info":[{"award-number":["KJZD-K201804701"]}]},{"name":"the Post Doc. Foundation of Heilongjiang Province","award":["LBH-Z17053"],"award-info":[{"award-number":["LBH-Z17053"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Velocity information from the odometer is the key information in a reduced inertial sensor system (RISS), and is prone to noise corruption. In order to improve the navigation accuracy and reliability of a 3D RISS, a method based on a tracking differentiator (TD) filter was proposed to track odometer velocity and acceleration. With the TD filter, an input signal and its differential signal are estimated fast and accurately to avoid the noise amplification that is brought by the conventional differential method. The TD filter does not depend on an object model, and has less computational complexity. Moreover, the filter phase lag is decreased by the prediction process with the differential signal of the TD filter. In this study, the numerical simulation experiments indicate that the TD filter can achieve a better performance on random noises and outliers than traditional numerical differentiation. The effectiveness of the TD filter on a 3D RISS is demonstrated using a group of offline data that were obtained from an actual vehicle experiment. We conclude that the TD filter can not only quickly and correctly filter velocity and estimate acceleration from the odometer velocity for a 3D RISS, but can also improve the reliability of the 3D RISS.<\/jats:p>","DOI":"10.3390\/s19204501","type":"journal-article","created":{"date-parts":[[2019,10,17]],"date-time":"2019-10-17T11:07:59Z","timestamp":1571310479000},"page":"4501","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Odometer Velocity and Acceleration Estimation Based on Tracking Differentiator Filter for 3D-Reduced Inertial Sensor System"],"prefix":"10.3390","volume":"19","author":[{"given":"Qing","family":"Zhang","sequence":"first","affiliation":[{"name":"College of Automation, Harbin Engineering University, Harbin 150001, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8803-910X","authenticated-orcid":false,"given":"Lianwu","family":"Guan","sequence":"additional","affiliation":[{"name":"College of Automation, Harbin Engineering University, Harbin 150001, China"}]},{"given":"Dexin","family":"Xu","sequence":"additional","affiliation":[{"name":"College of Automation, Harbin Engineering University, Harbin 150001, China"}]}],"member":"1968","published-online":{"date-parts":[[2019,10,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1111","DOI":"10.1016\/j.trc.2011.01.001","article-title":"Low cost two dimension navigation using an augmented Kalman filter\/Fast Orthogonal Search module for the integration of reduced inertial sensor system and Global Positioning System","volume":"19","author":"Shen","year":"2011","journal-title":"Transp. 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