Title :
Maximum likelihood optimal estimator of continuous nonlinear dynamic systems1
Author_Institution :
Rafael Adv. Defense Syst. Ltd., Haifa, Israel
Abstract :
The Joint Maximum Likelihood criterion is used to derive the optimal estimator for continuous nonlinear systems with nonlinear dynamics and measurement. The solution is explicit and gives recursive formulas of the optimal estimator. The computation of the estimator´s gains needs the solution of non-symmetric Differential Matrix Riccati Equation (DMRE). For linear systems this solution constitutes the structure of the Kalman Filter.
Keywords :
Kalman filters; Riccati equations; continuous systems; differential algebraic equations; linear systems; maximum likelihood estimation; nonlinear dynamical systems; nonlinear filters; optimisation; DMRE; Kalman filter; continuous nonlinear dynamic systems; estimator gains; joint maximum likelihood criterion; linear systems; maximum likelihood optimal estimator; measurement; nonsymmetric differential matrix Riccati equation; Equations; Jacobian matrices; Joints; Linear systems; Maximum likelihood estimation; Nonlinear dynamical systems; maximum likelihood; nonlinear estimator; nonlinear system; optimal estimator;
Conference_Titel :
Electrical & Electronics Engineers in Israel (IEEEI), 2014 IEEE 28th Convention of
Conference_Location :
Eilat
Print_ISBN :
978-1-4799-5987-7
DOI :
10.1109/EEEI.2014.7005795
