Adaptive navigation systems for an unmanned surface vehicle

Abstract

This paper reports the design of two potential navigation systems for use in an unmanned surface vehicle (USV) named Springer. The approaches adopted are based on fuzzy multisensor data fusion (MSDF) and multiple model adaptive estimation (MMAE) algorithms with adaptive capabilities. A general description of the Springer USV is given along with details of its navigation sensor suite. Of particular interest are the three different types of electronic compass used to supply heading information. Using a system identification technique, state space models of the compasses are derived for use in a simulation study to compare the navigation systems. From the results presented, it is concluded the fuzzy MSDF algorithm is better than the MMAE methodology in terms of heading (yaw error) accuracy and robustness. © 2011 2011 Taylor and Francis Group LLC.