A Recursive Least Squares Solution to Bearing-only Tracking, M.Sc. Thesis Sharif University of Technology ; Nayebi, Mohammd Mahdi (Supervisor)
Abstract
The conventional bearing-only tracking solutions are based on Kalman filter. Whenever the problem equations are nonlinear, Extended Kalman Filter (EKF) or more complicated methods are used necessarily. However, EKF suffers of being biased and unstable. Here a new recursive method based on a linear modeling of the problem is proposed, the method does not need an initial guess and outperforms the Kalman filter in the terms of accuracy, complexity and stability. Furthermore, input information needed for the proposed tracking filter is just the observer position, time and value of each angle measurements and the computation load is less than even a simple EKF. mathematical analysis, as well as...
Cataloging briefA Recursive Least Squares Solution to Bearing-only Tracking, M.Sc. Thesis Sharif University of Technology ; Nayebi, Mohammd Mahdi (Supervisor)
Abstract
The conventional bearing-only tracking solutions are based on Kalman filter. Whenever the problem equations are nonlinear, Extended Kalman Filter (EKF) or more complicated methods are used necessarily. However, EKF suffers of being biased and unstable. Here a new recursive method based on a linear modeling of the problem is proposed, the method does not need an initial guess and outperforms the Kalman filter in the terms of accuracy, complexity and stability. Furthermore, input information needed for the proposed tracking filter is just the observer position, time and value of each angle measurements and the computation load is less than even a simple EKF. mathematical analysis, as well as...
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