Fuzzy corrections in a GPS/INS hybrid navigation system

A. Hiliuta, R. Landry, F. Gagnon
<span title="">2004</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/a4fagdf2dnbrlghfkdsaomn6vm" style="color: black;">IEEE Transactions on Aerospace and Electronic Systems</a> </i> &nbsp;
A new concept regarding GPS/INS integration, based on artificial intelligence, i.e. adaptive neuro-fuzzy inference system (ANFIS) is presented. The GPS is used as reference during the time it is available. The data from GPS and inertial navigation system (INS) are used to build a structured knowledge base consisting of behavior of the INS in some special scenarios of vehicle motion. With the same data, the proposed fuzzy system is trained to obtain the corrected navigation data. In the absence
more &raquo; ... f the GPS information, the system will perform its task only with the data from INS and with the fuzzy correction algorithm. This paper shows, using Matlab simulations, that as long as the GPS unavailability time is no longer than the previous training time and for the scenarios a priori defined, the accuracy of trained ANFIS, in absence of data from a reference navigation system, is better than the accuracy of stand-alone INS. The flexibility of model is also analyzed. degrees in aerospace engineering from the Military Technical Academy, Bucharest, Romania. He was with the Romanian army, involved in flight testing for airplanes after major reparations. He was also a professor with the University of Craiova, Romania. In 2002 he worked as researcher in employing artificial intelligence to integrate different navigation systems. Since 2003 he is involved in projects regarding active aeroelastic wing developed byÉcole de Technologie Supérieure (ETS), Montréal, Canada with NASA Dryden Flight Research Center, and in the project development of a global model parameter with smart sensors, carried out by ETS with Bell Helicopter Textron under CRIAQ program. His research interests cover navigation systems and the integration techniques between complex systems, aeroservoelasticity, parameter estimation, digital signal processing, smart sensors, and smart architectures using MEMS.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/taes.2004.1310007">doi:10.1109/taes.2004.1310007</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/qnt6jng2tbhslmlw52i6nkrgti">fatcat:qnt6jng2tbhslmlw52i6nkrgti</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170808221325/http://lassena.etsmtl.ca/IMG/pdf/doc_106.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/94/ea/94ea10ab77c4a2ee799246dd4ac63c2419b0aaa7.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/taes.2004.1310007"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>