Because of the low estimation accuracy of normal extended Kalman filter(EKF)in strong nonlinear system,this pa-per developed an improved extended Kalman filter(MI-EKF)to solve the problem,and it improved the filtering accuracy great-ly.It proposed MI-EKF by combining multi-innovation theory and the standard EKF.MI-EKF had better precision and stability, because MI-EKF considered not only the current measured value,but also gave full consideration to the time before state of mo-tion.Finally,it discussed the impact of algorithm precision which included different numbers of innovations.Simulation results show that the improved algorithm MI-EKF included two innovations is optimal.%针对标准的扩展卡尔曼滤波算法（EKF）在强非线性系统中估计精度较低的问题，提出了一种改进的扩展卡尔曼滤波算法（MI-EKF），使得滤波精度得到很大的提高。MI-EKF 是在标准 EKF 基础上，结合多新息理论，不仅考虑了系统当前的测量值，而且也充分考虑了之前时刻的有用信息，从而使得 MI-EKF 的滤波精度和稳定性得到改善。最后，讨论了新息数量对改进算法精度的影响，仿真结果表明包含两个新息的 MI-EKF 算法滤波效果最佳。
展开▼
