Abstract
The integration of a feature based positioning sensor, rooted on Principal Component Analysis, with a Multi-Model Adaptive Estimator for Terrain Reference Navigation of Underwater Vehicles is proposed and discussed in detail. Resorting to a nonlinear Lyapunov transformation, the synthesis and analysis of each of the nonlinear multirate H 2 estimators is presented with overall guaranteed stability and optimal performance over equilibrium trajectories. Results from Monte Carlo simulation techniques to assess the performance of both the proposed feature based positioning sensor and estimation tools are included.
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