Using an empirical model of human turning motion to aid heading estimation in a personal navigation system

With the adoption of Global Navigation Satellite Systems in smart phones, soldier equipment, and emergency responder navigation systems users have realized the usefulness of low cost Personal Navigation Systems. The state-of-the-art Personal Navigation System is a unit that fuses information based on external references with a low cost IMU. Due to the size, weight, power, and cost constraints imposed on a pedestrian navigation systems as well as current IMU performance limitations, the gyroscopes used to determine heading exhibit significant drift limiting the performance of the navigation system. In this thesis biomechanical signals are used to predict the onset of pedestrian turning motion. Experimental data from eight subjects captured in a gait laboratory using a Vicon motion tracking unit is used for validation. The analysis of experimental data shows the heading computed by turn prediction augmented integration is more accurate than open loop gyro integration alone.

Author dc:creator

• Jakel, Tom Bryan

• Algorithm
• Inertial
• Navigation
• Pedestrian
• Personal
• Reckoning

Language dc:language.iso

en_US

Handle dc:identifier.uri

http://hdl.handle.net/11299/162354

OAI identifier oai:identifier

oai:conservancy.umn.edu:11299/162354