Passive target tracking using nonlinear estimation theory.
Da Cunha, Marcilio Boavista
Kirk, Donald E.
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The problem of tracking submarine targets with passive sonobuoys is mathematically modelled. A comprehensive study is made of all the information available in the acoustic signals picked up by the sonobuoys and of the usefulness of this information in the estimation process. The presence of nonlinearities in the tracking model leads to the application of nonlinear estimation theory. Bayes formulation concepts are applied to generate approximate solutions and filtering algorithms, and the well known extended Kalman filter equations and higher order filtering algorithms are obtained from this approach. The concept of partitioning the measurements is presented and shown to bring advantages in computing efficiency and also, for nonlinear measurements, in tracking accuracy. A graphical interpretation of the action of Kalman filters is developed and provides insight into the importance of each variable in the filtering process. Extensive simulations, designed to test the performance of the algorithms developed, are presented in graphical form and analyzed. (Author)
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