This report considers the vehicle navigation problem for an autonomous underwater vehicle with six degrees of freedom. We approach this problem using an error state formulation of the Kalman filter. Integration of the vehicle's high-rate inertial measurement unit's accelerometers and gyros allow time propagation while other sensors provide measurement corrections. The low-rate aiding sensors include a Doppler velocity log, an acoustic long baseline system that provides round-trip travel times from known locations, a pressure sensor for aiding depth, and an attitude sensor. Measurements correct the filter independently as they arrive, and as such, the filter is not dependent on the arrival of any particular measurement. The navigation system can estimate critical bias parameters that improve performance. The result is a robust navigation system. Simulation and experimental results are provided.
Autonomous Underwater Vehicle Navigation
2008
36 pages
Report
Keine Angabe
Englisch
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