Abstract
To improve the low state estimation accuracy of nonlinear state estimation due to large initial estimation error and nonlinearity of measurement equation, we obtain Levenberg-Marquardt (abbr. L-M) method based iteration square root cubature Kalman filter (ISRCKFLM) combining the measurement update of square root cubature Kalman filter (SRCKF) with nonlinear least square error, so the ISRCKFLM algorithm has the virtues of global convergence and numerical stability. We apply the ISRCKFLM algorithm to state estimation for re-entry ballistic target; the simulation results demonstrate the ISRCKFLM algorithm has better accuracy of state estimation.
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