针对当前自适应组合导航系统算法的研究趋势，总结了卡尔曼滤波技术的缺陷和利用智能融合技术提高滤波器性能的设计思想。
The adaptive Kalman filtering (AKF) based on intelligent information fusion algorithm has currently became an effective approach to enhance the integrated navigation system's robustness and accuracy.
本文以卡尔曼滤波跟踪算法为例，重点讨论了跟踪数据率随采样时间和所测目标距离的变化趋势。
With the Kalman filter as an instantiation, the changing of the data rate factor along with sample time and distance of target is studied.
本文以卡尔曼滤波跟踪算法为例，重点讨论了跟踪数据率随采样时间和所测目标距离的变化趋势。
With the Kalman filter as an instantiation, the changing of the data rate factor along with sample time and distance of target is studied.
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