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中文摘要：
针对扩展卡尔曼滤波（EKF）线性化所产生的线性化模型误差问题,使用非线性预测滤波对线性化所引起的模型误差进行预测,并在标准EKF的解算过程中考虑到预测所得误差的统计特性,使模型更趋于真实情况。通过算例对改进算法的性能进行了验证。
英文摘要：
Extended Kalman filtering（EKF） is an effective method for nonlinear problem.However,linearization error is introduced in the process of transforming the nonlinear problem to the linear one.For the linear model error problem,the nonlinear predictive filtering（NPF） is used to predict the linear model error in the nonlinear problem,which is caused by extended Kalman filtering（EKF）.The statistic properties of predicted model errors is combined with the process noise in the standard EKF to make the model more exact.Lastly,the performance of NPEKF and EKF is compared by an simulation example.The results show the validity of the compensation algorithm of model errors.
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