{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T16:00:16Z","timestamp":1777910416168,"version":"3.51.4"},"reference-count":44,"publisher":"SAGE Publications","issue":"1","license":[{"start":{"date-parts":[[2018,4,10]],"date-time":"2018-04-10T00:00:00Z","timestamp":1523318400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Transactions of the Institute of Measurement and Control"],"published-print":{"date-parts":[[2019,1]]},"abstract":"<jats:p>\n                    Attitude estimation is one of the core fundamentals for navigation of unmanned vehicles and other robotic systems. With the advent of low cost and low accuracy micro-electro-mechanical systems (MEMS) based inertial sensors, these devices are used ubiquitously for all such commercial grade systems that need motion information. However, these sensors suffer from time-varying bias and noise parameters, which need to be compensated during system state estimation. Complementary filtering is one of such techniques that is used here for estimating attitude of a moving vehicle. However, the complementary filter structure is dependent on user fed gain parameters, K\n                    <jats:sub>P<\/jats:sub>\n                    and K\n                    <jats:sub>I<\/jats:sub>\n                    and needs a mechanism by which they can be obtained automatically. In this paper, an attempt has been made towards addressing this issue by applying least square estimation technique on the error obtained between estimated and measured attitude angles. The proposed algorithm simplifies the design of nonlinear complementary filter by computing the filter gains automatically. The experimental investigation has been carried out over several datasets, confirming the advantage of obtaining gain parameters automatically for the complementary filtering structure.\n                  <\/jats:p>","DOI":"10.1177\/0142331218755234","type":"journal-article","created":{"date-parts":[[2018,4,10]],"date-time":"2018-04-10T09:08:13Z","timestamp":1523351293000},"page":"235-245","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":19,"title":["Least square estimation-based adaptive complimentary filter for attitude estimation"],"prefix":"10.1177","volume":"41","author":[{"given":"Parag","family":"Narkhede","sequence":"first","affiliation":[{"name":"Symbiosis Institute of Technology, Symbiosis International (Deemed University), India"}]},{"given":"Alex Noel","family":"Joseph Raj","sequence":"additional","affiliation":[{"name":"College of Engineering, Shantou University, China"}]},{"given":"Vipan","family":"Kumar","sequence":"additional","affiliation":[{"name":"CSIR-Central Scientific Instruments Organization, India"},{"name":"Academy of Scientific and Innovative Research, India"}]},{"given":"Vinod","family":"Karar","sequence":"additional","affiliation":[{"name":"CSIR-Central Scientific Instruments Organization, India"},{"name":"Academy of Scientific and Innovative Research, India"}]},{"given":"Shashi","family":"Poddar","sequence":"additional","affiliation":[{"name":"CSIR-Central Scientific Instruments Organization, India"},{"name":"Academy of Scientific and Innovative Research, India"}]}],"member":"179","published-online":{"date-parts":[[2018,4,10]]},"reference":[{"key":"bibr1-0142331218755234","doi-asserted-by":"publisher","DOI":"10.1590\/S0104-65002009000300003"},{"key":"bibr2-0142331218755234","doi-asserted-by":"publisher","DOI":"10.1002\/j.2161-4296.1972.tb01706.x"},{"key":"bibr3-0142331218755234","volume-title":"Introduction to Random Signals and Applied Kalman Filtering: with MATLAB Exercises and Solutions","author":"Brown RG","year":"1997"},{"key":"bibr4-0142331218755234","doi-asserted-by":"publisher","DOI":"10.1109\/ICARSC.2015.33"},{"key":"bibr5-0142331218755234","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2011.6094432"},{"issue":"2","key":"bibr6-0142331218755234","first-page":"43","volume":"21","author":"Corke P","year":"2004","journal-title":"Journal of Field Robotics"},{"key":"bibr7-0142331218755234","doi-asserted-by":"publisher","DOI":"10.2514\/1.22452"},{"key":"bibr8-0142331218755234","doi-asserted-by":"publisher","DOI":"10.1201\/9781315371160"},{"key":"bibr9-0142331218755234","volume-title":"Multisensor Attitude Estimation: Fundamental Concepts And Applications","author":"Elkaim GH","year":"2016"},{"key":"bibr10-0142331218755234","volume-title":"An Application of UAV Attitude Estimation Using a Low-Cost Inertial Navigation System","author":"Eure KW","year":"2013"},{"key":"bibr11-0142331218755234","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2008.4650766"},{"key":"bibr12-0142331218755234","doi-asserted-by":"publisher","DOI":"10.1109\/ROBOT.2006.1642025"},{"key":"bibr13-0142331218755234","first-page":"1096","volume-title":"Proceedings of the 17th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2004)","author":"Hide C","year":"2004"},{"key":"bibr14-0142331218755234","doi-asserted-by":"publisher","DOI":"10.1109\/TAES.1975.308081"},{"key":"bibr15-0142331218755234","doi-asserted-by":"publisher","DOI":"10.1016\/S0924-4247(03)00353-4"},{"key":"bibr16-0142331218755234","doi-asserted-by":"publisher","DOI":"10.2514\/1.53467"},{"key":"bibr17-0142331218755234","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2003.823141"},{"issue":"12","key":"bibr18-0142331218755234","first-page":"1541","volume":"3","author":"Kim JH","year":"2009","journal-title":"World Academy of Science, Engineering and Technology, International Journal of Mechanical and Mechatronics Engineering"},{"key":"bibr19-0142331218755234","doi-asserted-by":"publisher","DOI":"10.1016\/j.ast.2017.07.011"},{"key":"bibr20-0142331218755234","doi-asserted-by":"publisher","DOI":"10.1016\/j.ast.2015.12.025"},{"key":"bibr21-0142331218755234","unstructured":"Madgwick SO Open Source IMU And AHRS Algorithms. 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