LOCAL-AREA NAVIGATION USING SONAR FEATURE-EXTRACTION AND MODEL-BASED PREDICTIVE CONTROL

This paper demonstrates a method to navigate an autonomous underwater vehicle in a local area using an acoustic sensor for position informat ion derived from feature detection. A dynamic model of the vehicle res ponse is used for control between location updates. Favorable results have been found using this approach, and precision positioning of the vehicle to centimeters has been accomplished. Another part of the prob lem is the need to provide a high-frequency update of vehicle position in order to close the positioning servo loops. Using sonar image feat ure extraction is necessarily time consuming and therefore is performe d in a tactical level process providing asynchronous data to the tacti cal navigator. It follows that some form of fast dead reckoning must b e performed in the execution level either by INS-Doppler or by water s peed and heading data or by a model-based predictor. This paper deals with the use of model-based predictor technique where knowledge of the dynamic model of the vehicle provides state information to the vehicl e positioning control function. The model uncertainty provides errors of course, but these are corrected through asynchronous updates from t he feature extracted positions in the tactical level sonar manager. Th is concept has been verified by both simulation studies and by experim ental validation with the Naval Postgradual School Phoenix vehicle.