Weighted Minimum Mean Square Kalman Filter
基于加权最小二乘的卡尔曼滤波算法

In order to use Kalman Filter (KF) in nonlinear systems, a new method was proposed. Using the principle that a set of discretely sampled points can be used to form a linear system, the estimator yields performance ectuivalent to the Extended Kalman Filter (EKF) for nonlinear systems and can be elegantly used to nonlinear systems without the differential steps required by the EKF. We argue that the ease of implementation and more accurate estimation features of the new filter recommend its use in applications.