The iterated divided difference filter

With an application to target tracking, the iterated divided difference filter is presented. In new algorithm, an iterated measurement update was proposed to improve the approximation accuracy of the nonlinear state estimation. When iterating, the current mean and the covariance of the divided difference filter (DDF) were used to measurement update procedure. The simulations show that iterated DDF is capable of providing better performance than the standard DDF, especially in the case of significant nonlinearity in the system function.