Title :
Model-based localization for a shallow ocean experiment
Author :
Candy, J.V. ; Sullivan, E.J.
Author_Institution :
Lawrence Livermore Nat. Lab., CA, USA
Abstract :
A model-based approach is developed to solve the passive localization problem in ocean acoustics using the state-space formulation. It is shown that the inherent structure of the resulting processor consists of a parameter estimator coupled to a nonlinear optimization scheme. The parameter estimator is designed using an ocean acoustic propagation model in developing the model-based identifier required for localization
Keywords :
adaptive Kalman filters; adaptive estimation; oceanographic techniques; optimisation; parameter estimation; position measurement; sonar signal processing; state-space methods; underwater sound; EKF; acoustic propagation model; adaptive model-based solution; model-based identifier; model-based localization; nonlinear optimization scheme; ocean acoustics; parameter estimator; passive localization problem; polytope approach; range-depth function; shallow ocean experiment; signal enhancement; sonar signal processing; source position location estimation; state-space formulation; Acoustic propagation; Acoustic signal detection; Couplings; Nonlinear acoustics; Oceans; Parameter estimation; Power system modeling; Predictive models; Sonar detection; Underwater acoustics;
Conference_Titel :
OCEANS '95. MTS/IEEE. Challenges of Our Changing Global Environment. Conference Proceedings.
Print_ISBN :
0-933957-14-9
DOI :
10.1109/OCEANS.1995.528547
