A study on indoor pedestrian localization algorithms with foot-mounted sensors

The work presents a foot-mounted sensor system for a combined indoor/outdoor pedestrian localization. The approach is based on a zero-velocity update scheme formulated as an Extended or Unscented Kalman filter with quaternion orientation representation and employs a custom low-cost sensor unit. Both filters are compared in terms of speed and accuracy on a representative trajectory. A detailed discussion is provided with respect to different filter state formulations, stance still detection mechanisms and associated filter parameters. The presented pure inertial system is augmented with magnetic field measurements for heading correction. The challenging localization scenario with an elevator is addressed by augmenting the system with a barometric pressure sensor for height error correction. The work also demonstrates how the basic algorithm version can be extended with reference systems such as GPS and passive RFID tags on the floor for absolute position drift correction.