Design and Implementation of an Inertial Navigation System for Pedestrians Based on a Low-Cost MEMS IMU
This addresses drift issues for pedestrian navigation in infrastructure-less environments, offering a cost-effective solution, though it is incremental in improving existing methods.
The paper tackles drift in pedestrian inertial navigation using low-cost MEMS IMUs by proposing a novel method that integrates sensor error modeling and soft heuristic stance detection, achieving similar or better performance compared to existing systems without requiring magnetometers.
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.