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Hybrid State Estimators for the Control of Remotely Operated Underwater Vehicles

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Master's thesis,

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This thesis explores the use of hybrid state estimators to increase the accuracy and flexibility of acoustic position measurement systems used to control underwater vehicles. Two different approaches to extend the range of acoustic position measurement systems are explored. The first uses an inexpensive strapdown inertial measurement system to augment the acoustic with inertial position information. This approach is based on experience gained using an attitude and inertial measurement package fielded on the JASON JUNIOR remotely Operated Vehicle ROV. The second approach uses a mobile, platform- mounted, acoustic net in conjunction with a platform tracking system. This second investigation used the JASON ROV as the basis for the simulation work. Some of the theoretical and practical difficulties encountered when range is extended using an augmented system are explored. Simulation results are used to demonstrate the effects of these difficulties on position estimation accuracy and on the performance in closed loop control of the vehicle. Using measured sensor noise characteristics, a hybrid Kalman filter is developed for each approach to take the greatest advantage of the available information. Formulation of the Kalman filter is different for each case. In the 2nd case, the geographic position of the ROV is the sum of the acoustic nets geographic position, measured at a different interval by an RF positioning system, and the position of the ROV relative to the net, as measured acoustically. edc

Subject Categories:

  • Acoustic Detection and Detectors
  • Underwater and Marine Navigation and Guidance

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