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Data fusion algorithms for multiple inertial measurement units.
Jared B Bancroft1, Gérard Lachapelle
1Department of Geomatics Engineering, Schulich School of Engineering, University of Calgary, 2500 University Drive NW, Calgary, AB T2N 1N4, Canada. j.bancroft@ucalgary.ca
Sensors (Basel, Switzerland)
|December 14, 2011
Summary
Multiple inertial measurement units (IMUs) improve pedestrian navigation systems. This study evaluates three fusion algorithms, comparing their accuracy and availability to enhance Global Positioning System (GPS) performance in challenging environments.
Area of Science:
- * Navigation Systems
- * Sensor Fusion
- * Signal Processing
Background:
- * Pedestrian navigation systems commonly integrate a single inertial measurement unit (IMU) with Global Positioning System (GPS) receivers.
- * Enhancing navigation accuracy and availability, especially during GPS signal attenuation, remains a key challenge.
- * Multiple IMUs offer potential for improved performance, but optimal fusion strategies require investigation.
Purpose of the Study:
- * To develop and evaluate multiple IMU fusion algorithms for pedestrian navigation.
- * To analyze the benefits and drawbacks of different fusion methods in terms of accuracy and availability.
- * To compare proposed algorithms against existing virtual IMU (VIMU) architectures.
Main Methods:
- * Implemented three fusion algorithms: a virtual IMU (VIMU) approach, a stacked filter, and a federated filter.
- * Mapped raw IMU measurements to a common frame for Kalman filtering in the VIMU method.
- * Utilized relative IMU information for updates in the stacked filter and employed local/master filters in the federated approach.
Main Results:
- * Performance was evaluated based on accuracy and availability in environments with moderate and severe GPS signal attenuation.
- * Accuracy was analyzed as a function of filter architecture and the number of IMUs employed.
- * Proposed fusion methods demonstrated potential for enhancing navigation solution reliability.
Conclusions:
- * Multiple IMU integration and advanced fusion algorithms can significantly improve pedestrian navigation system performance.
- * The choice of fusion architecture impacts accuracy and availability, particularly under degraded GPS conditions.
- * Further research into optimized fusion strategies is warranted for robust pedestrian navigation solutions.
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