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I’m walking here! Checking the accuracy of an inertial-based pedestrian navigation system with a drone / Marcin Uradzinski in GPS world, vol 28 n° 6 (June 2017)

Public [article]  inGPS world > vol 28 n° 6 (June 2017) . - pp 58 - 64 Titre : I’m walking here! Checking the accuracy of an inertial-based pedestrian navigation system with a drone Type de document : Article/Communication Auteurs : Marcin Uradzinski, Auteur ; Hang Guo, Auteur ; Clifford Mugnier, Auteur Année de publication : 2017 Article en page(s) : pp 58 - 64 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement [Termes IGN] drone [Termes IGN] filtre de Kalman [Termes IGN] navigation à l'estime [Termes IGN] navigation pédestre [Termes IGN] piéton [Termes IGN] positionnement en intérieur Résumé : (Auteur) Satellite navigation systems have achieved great success in personal positioning applications. Nowadays, GNSS is an essential tool for outdoor navigation, but locating a user’s position in degraded and denied indoor environments is still a challenging task. During the past decade, methodologies have been proposed based on inertial sensors for determining a person’s location to solve this problem. One such solution is a personal pedestrian dead reckoning (PDR) system, which helps in obtaining a seamless indoor/outdoor position. Built-in sensors measure the acceleration to determine pace count and estimate the pace length to predict position with heading information coming from angular sensors such as magnetometers or gyroscopes. PDR positioning solutions find many applications in security monitoring, personal services, navigation in shopping centers and hospitals and for guiding blind pedestrians. Several dead-reckoning navigation algorithms for use with inertial measurement units (IMUs) have been proposed. However, these solutions are very sensitive to the alignment of the sensor units, the inherent instrumental errors, and disturbances from the ambient environment - problems that cause accuracy to decrease over time. In such situations, additional sensors are often used together with an IMU, such as ZigBee radio beacons with position estimated from received signal strength. In this article, we present a PDR indoor positioning system we designed, tested and analyzed. It is based on the pace detection of a foot-mounted IMU, with the use of extended Kalman filter (EKF) algorithms to estimate the errors accumulated by the sensors. Numéro de notice : A2017-294 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85332 [article]