Gyroscope Calibration and Dead Reckoning for an Autonomous Underwater Vehicle

Abstract

Autonomous Underwater Vehicles (AUVs) are currently being used for many underwater tasks such as mapping underwater terrain, detection of underwater objects, and assessment of water quality. Possible uses continue to grow as the vehicles become smaller, more agile, and less expensive to operate. However, trade-offs exist between making less expensive, miniature AUVs and the quality at which they perform. One area affected by cost and size is the onboard navigation system. To achieve the challenges of low-cost rate sensors, this thesis examines calibration methods that are suitable for identifying calibration coefficients in low-cost MEMS gyros.

A brief introduction to underwater navigation is presented and is followed by the development of a model to describe the operation of a rate gyro. The model uses the integral relationship between angular rate and angular position measurements. A compass and two tilt sensors provide calibrated angular position data against which the three single axis gyros are compared to obtain an error signal describing errors present in the angular rate measurements.

A calibration routine that adaptively identifies error parameters in the gyros is developed. Update laws are chosen to recursively apply estimated error parameters to minimize the system error signal. Finally, this calibration method is applied to a simple dead reckoning algorithm in an attempt to measure the improvements calibration provides.