中文摘要：

应用常规卡尔曼滤波器（KF）要求知道系统精确的数学模型和系统噪声与量测噪声的统计特性，才能获得理想的滤波效果，否则可能产生发散现象.人们越来越倾向于利用自适应滤波（AKF）技术来解决发散的问题.针对AKF技术的研究现状，本文探讨一种结构简单、实时性较强、工程上比较实用的AKF算法.仿真结果表明，这种算法具有较强的自适应性，为一种实用而有效的滤波方法.

英文摘要：

Knowledge of an accurate mathematical model and the statistical characteristics of system noise and measuring noise is required to get a desired filtering effect during use of conventional Kalman filters. Otherwise, it will result in diffusion. Therefore, adaptive Kalman filter technology is more and more used. This paper proposes a practical adaptive Kalman filter algorithm featuring simplified architecture and powerful realtime performance. Simulation results show that the algorithm is highly adaptive and is a practical and effective filtering method.