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基于扩展增量Kalman滤波方法(EIKF)和自适应增量Kalman滤波(AIKF),建立自适应扩展增量Kalman(AEIKF)模型及其分析方法,给出递推算法.在许多实际情况(如深空探测),由于环境因素的影响、测量设备的不稳定性等原因,量测方程往往存在未知的系统误差,并且模型参数也具有不确定性,结果导致较大的Kalman滤波误差,影响滤波的收敛性.提出的AEIKF方法能够成功消除这种未知的系统误差,并能够实时估计变化的噪声统计量,提高Kalman滤波精度.该方法计算简单,便于工程应用.
Based on Extended Incremental Kalman Filter (EIKF) and Adaptive Incremental Kalman Filter (AIKF), an adaptive extended Kalman (AEIKF) model and its analysis method are established and a recursive algorithm is given. In many practical situations Air detection), due to environmental factors, the instability of measuring equipment and other reasons, the measurement equation often there is unknown system error, and the model parameters are also uncertain, resulting in a larger Kalman filter error, the impact of filtering Convergence.The proposed AEIKF method can successfully eliminate this unknown systematic error, and can estimate the noise statistics in real time and improve the Kalman filtering accuracy.The method is simple and easy to be applied in engineering.