Inertial navigation systems for pedestrians are infrastructure-less and can achieve sub-meter accuracy in the short/medium period. However, when low-cost inertial measurement units (IMU) are employed for their implementation, they suffer from a slowly growing drift between the true pedestrian position and the corresponding estimated position. In this paper we illustrate a novel solution to mitigate such a drift by: a) using only accelerometer and gyroscope measurements (no magnetometers required); b) including the sensor error model parameters in the state vector of an extended Kalman filter; c) adopting a novel soft heuristic for foot stance detection and for zero-velocity updates. Experimental results evidence that our inertial-only navigation system can achieve similar or better performance with respect to pedestrian dead-reckoning systems presented in related studies, although the adopted IMU is less accurate than more expensive counterparts.
Design and implementation of an inertial navigation system for pedestrians based on a low-cost MEMS IMU / Montorsi, Francesco; Pancaldi, Fabrizio; Vitetta, Giorgio Matteo. - STAMPA. - (2013), pp. 57-61. (Intervento presentato al convegno 2013 IEEE International Conference on Communications Workshops, ICC 2013 tenutosi a Budapest, hun nel June, 9-13) [10.1109/ICCW.2013.6649201].
Design and implementation of an inertial navigation system for pedestrians based on a low-cost MEMS IMU
MONTORSI, FRANCESCO;PANCALDI, Fabrizio;VITETTA, Giorgio Matteo
2013
Abstract
Inertial navigation systems for pedestrians are infrastructure-less and can achieve sub-meter accuracy in the short/medium period. However, when low-cost inertial measurement units (IMU) are employed for their implementation, they suffer from a slowly growing drift between the true pedestrian position and the corresponding estimated position. In this paper we illustrate a novel solution to mitigate such a drift by: a) using only accelerometer and gyroscope measurements (no magnetometers required); b) including the sensor error model parameters in the state vector of an extended Kalman filter; c) adopting a novel soft heuristic for foot stance detection and for zero-velocity updates. Experimental results evidence that our inertial-only navigation system can achieve similar or better performance with respect to pedestrian dead-reckoning systems presented in related studies, although the adopted IMU is less accurate than more expensive counterparts.Pubblicazioni consigliate
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