This work examines the design of a Kalman filter based navigation algorithm for the Canadian Scientific Submersible Facility's (CSSF) ROPOS ROV. The 5000m ROV is typically hired by scientists to deploy and recover small scientific instrumentation packages on the sea floor, and collect subsea biological and geological samples. To efficiently complete these tasks a navigation system that can provide a global positioning accuracy of +/-2.5m is required. However. the ROPOS navigation system presently relies on noisy USBL acoustic positioning measurements (+/- 15m at 2500m). To overcome the limitations of the USBL signal and increase the navigation system accuracy. it is proposed that a depth sensor, Doppler velocity log and OCTANS gyrocompass be used in conjunction with a model-based extended Kalman filter (EKF) algorithm to provide a single navigation data stream.

To examine the efficacy of the proposed solution. non-linear models of the ROPOS ROV and its tether are presented. Parameters are identified for both the ROPOS and tether models, and the models are coupled. permitting realistic dynamic simulation of the ROPOS system. A virtual pilot, based on a PID automatic control scheme. is created to fly the virtual ROPOS vehicle between waypoints in the simulation. An instrument simulator is developed that is capable of producing asynchronous measurement data from virtual instruments. Using this simulation facility, realistic ROPOS maneuvers are executed. During the simulations, ROPOS' virtual instruments (depth sensor, DVL, USBL and OCTANS) produce pseudo-measurements that are typical of the real ROPOS sensor suite. These measurements are fed to the EKF navigation algorithm.

This work successfully showed that the EKF filter framework can be used to blend ROPOS's asynchronous sensor data, such that a navigation accuracy of ≈2.5m RMS is produced. It is found that without the OCTANS instrument. the advanced ROV process model permits robust filter operation. even in cases of USBL and/or DVL drop-out. In the case where the OCTANS instrument is providing velocity data, the filter does not require an advanced ROV process model within the EKF in order to maintain filter accuracy during USBL and DVL dropout. Rather. accuracy is sufficiently maintained with a simple constant velocity model of the vehicle motion. However, it was also shown that the ROPOS velocity signal estimation can be greatly enhanced by the advanced ROPOS process model. It was also found that that the tether effects are paramount in the advanced ROPOS process model. When the tether disturbances are not sensed. the advanced model position-estimation performance is equivalent to a constant velocity process model.