A method on parameter estimation of nonlinear systems

It is developed that the state estimation of nonlinear system model based on maximum a posteriori (MAP) estimation. This is equivalent to the minimization problem of the object function derived from a posteriori probability density function.It is shown that the minimizer based on Newton-method becomes to iterated extended Kalman filter (IEKF). A method on the gain adjustment of the MAP estimator is given so as to improve the performance of it. Then a method of the parameter setting for the gain adjustment is given.