{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,2]],"date-time":"2025-03-02T14:40:16Z","timestamp":1740926416926,"version":"3.38.0"},"reference-count":40,"publisher":"SAGE Publications","issue":"6","license":[{"start":{"date-parts":[[2020,10,8]],"date-time":"2020-10-08T00:00:00Z","timestamp":1602115200000},"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":["Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering"],"published-print":{"date-parts":[[2021,7]]},"abstract":"<jats:p> In most applications of autonomous navigation, the state of a system must be estimated from noisy sensors. Accurate estimation of the true system state can be achieved using data fusion algorithms. Furthermore, the fusion scheme can be affected by many factors such as modeling errors and parameters uncertainties. The gaps and inconsistencies due to the sensors noise and modeling errors can be reached with robust nonlinear filtering. In this article, a new framework has been developed for data fusion algorithms based on nonlinear NH\u221e filter with fuzzy adaptive bound and adaptive disturbances attenuations. Type-1 Fuzzy Adaptive NH<jats:sub>\u221e<\/jats:sub> algorithm has been proposed and compared with the Interval Type 2 Fuzzy Adaptive NH<jats:sub>\u221e<\/jats:sub>, for unmanned vehicle localization. The proposed algorithms fuse data from low-cost sensors using inertial navigation system, Global Positioning System and monocular vision. Type-1 Fuzzy Adaptive NH<jats:sub>\u221e<\/jats:sub> and Interval Type 2 Fuzzy Adaptive NH<jats:sub>\u221e<\/jats:sub> algorithms, adaptively, handle the effects of noisy sensors, parameters uncertainties and modeling errors. Both algorithms use adaptive bounds [Formula: see text] and adaptive disturbance attenuation [Formula: see text] for higher-order terms of the Taylor development. The adaptive bounds consider issues associated to Gyro drift, image distortion and Global Positioning System dilution of precision which make the proposed algorithms more accurate than the classical NH\u221e. The validating experiment and the efficiency of Type-1 Fuzzy Adaptive NH<jats:sub>\u221e<\/jats:sub> and Interval Type 2 Fuzzy Adaptive NH<jats:sub>\u221e<\/jats:sub> have been conducted in real scenario and in unstructured outdoor environment without any a priori knowledge of the evolution of the vehicle. The experimental results have demonstrated the robustness and efficiency of these two filtering strategies against uncertainties and their online sensor switching capability. The Interval Type 2 Fuzzy Adaptive NH<jats:sub>\u221e<\/jats:sub> algorithm provides more accuracy and robustness compared to the Type-1 Fuzzy Adaptive NH<jats:sub>\u221e<\/jats:sub>. <\/jats:p>","DOI":"10.1177\/0959651820961603","type":"journal-article","created":{"date-parts":[[2020,10,8]],"date-time":"2020-10-08T08:56:04Z","timestamp":1602147364000},"page":"881-897","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":2,"title":["Multi-sensor fusion approach based on nonlinear H\u221e filter with interval type 2 fuzzy adaptive parameters tuning for unmanned vehicle localization"],"prefix":"10.1177","volume":"235","author":[{"given":"Fariz","family":"Outamazirt","sequence":"first","affiliation":[{"name":"\u00c9cole Militaire Polytechnique, Algiers, Algeria"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8089-9981","authenticated-orcid":false,"given":"Djabir","family":"Djaidja","sequence":"additional","affiliation":[{"name":"\u00c9cole Militaire Polytechnique, Algiers, Algeria"}]},{"given":"Chouaib","family":"Boudjimar","sequence":"additional","affiliation":[{"name":"\u00c9cole Militaire Polytechnique, Algiers, Algeria"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4203-6357","authenticated-orcid":false,"given":"Kahina","family":"Louadj","sequence":"additional","affiliation":[{"name":"Laboratoire de Conception et Conduites des Syst\u00e8mes de Production (L2CSP), Tizi-Ouzou, Algeria"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9961-7462","authenticated-orcid":false,"given":"Abdelkrim","family":"Nemra","sequence":"additional","affiliation":[{"name":"\u00c9cole Militaire Polytechnique, Algiers, Algeria"}]},{"given":"Fu","family":"Li","sequence":"additional","affiliation":[{"name":"School of Automation Science and Electrical Eng, Beihang University, Beijing, China"}]},{"given":"Lin","family":"Yan","sequence":"additional","affiliation":[{"name":"School of Automation Science and Electrical Eng, Beihang University, Beijing, China"}]}],"member":"179","published-online":{"date-parts":[[2020,10,8]]},"reference":[{"volume-title":"INS\/CNS\/GNSS integrated navigation technology","year":"2011","author":"Quan W","key":"bibr1-0959651820961603"},{"volume-title":"Elevation effects on GPS positional accuracy","year":"1998","author":"Heselton RR","key":"bibr2-0959651820961603"},{"first-page":"1403","volume-title":"Proceedings Ninth IEEE international conference on computer vision","author":"Davison AJ","key":"bibr3-0959651820961603"},{"key":"bibr4-0959651820961603","doi-asserted-by":"publisher","DOI":"10.1109\/70.938382"},{"key":"bibr5-0959651820961603","doi-asserted-by":"publisher","DOI":"10.1109\/MRA.2006.1638022"},{"key":"bibr6-0959651820961603","doi-asserted-by":"publisher","DOI":"10.1109\/TRO.2012.2235699"},{"volume-title":"Bearings-only localization and mapping","year":"2005","author":"Deans MC","key":"bibr7-0959651820961603"},{"first-page":"1260","volume-title":"2015 international conference on unmanned aircraft systems (ICUAS)","author":"Huang R","key":"bibr8-0959651820961603"},{"key":"bibr9-0959651820961603","doi-asserted-by":"publisher","DOI":"10.5772\/43"},{"key":"bibr10-0959651820961603","doi-asserted-by":"publisher","DOI":"10.11113\/elektrika.v18n3-2.193"},{"volume-title":"Proceedings of the AAAI National Conference on Artificial Intelligence","author":"Montemerlo M","key":"bibr11-0959651820961603"},{"first-page":"382","volume-title":"IEEE\/RSJ international conference on intelligent robots and systems","author":"Saarinen J","key":"bibr12-0959651820961603"},{"key":"bibr13-0959651820961603","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2016.03.026"},{"key":"bibr14-0959651820961603","doi-asserted-by":"publisher","DOI":"10.3390\/s140917600"},{"key":"bibr15-0959651820961603","doi-asserted-by":"publisher","DOI":"10.1109\/TFUZZ.2012.2201728"},{"key":"bibr16-0959651820961603","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4614-6666-6_2"},{"key":"bibr17-0959651820961603","first-page":"1","author":"Mendel JM","year":"2009","journal-title":"IEEE SMC eNewsletter"},{"key":"bibr18-0959651820961603","doi-asserted-by":"publisher","DOI":"10.1109\/JSEN.2009.2034730"},{"key":"bibr19-0959651820961603","unstructured":"Blewitt G. 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