目前，基于卡尔曼滤波理论设计的组合导航系统有效提高了导航系统的性能价格比。
Nowadays integrated navigation system based on Kalman Filtering theory has efficiently increased the cost performance ratio.
鉴于常规卡尔曼滤波算法组合导航系统数据融合算法中，存在易于发散的缺陷，尝试将遗传优化人工神经网络引入组合导航系统中。
As the conventional Kalman filter is liable to get divergence in integrated navigation system data fusion, an artificial neural network based on the genetic algorithms was applied in the system.
采用了卡尔曼滤波为核心算法的数据融合，来提高组合导航系统的定位精度和可靠性。
This system takes the Kalman filter as core algorithm to fuse data so that the positioning accuracy and system reliability can be improved.
提出了一种利用模糊逻辑控制器来在线调节卡尔曼滤波器的自适应数据融合方法，并着重研究了其在GPS/INS组合导航中的应用。
This paper presents an adaptive data fusion method which uses a fuzzy logic controller to online adjust the Kalman filter, and focuses on its application to the integrated GPS/INS navigation.
第三章，建立了卫星轨道动力学模型，设计了GPS和运动方程组合的卡尔曼滤波器，并针对不同轨道高度的微小卫星进行了定位仿真。
In chapter 3, the orbit dynamics models are established, the Kalman Filter of the GPS and kinematics equation combined are designed, and simulations of different orbit Micro-satellite are done.
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.
着重介绍了卡尔曼滤波器技术的原理、计算公式、模拟方法以及在组合导航系统中的应用。
The result of computer simulation in the GPS/INS integrated system shows that the algorithm is useful and effective with high effectiveness.
着重介绍了卡尔曼滤波器技术的原理、计算公式、模拟方法以及在组合导航系统中的应用。
The result of computer simulation in the GPS/INS integrated system shows that the algorithm is useful and effective with high effectiveness.
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