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SINS/GPS/CNS Integrated Navigation Method Study Based on Federated Filter

机译:基于联合滤波器的SINS / GPS / CNS组合导航方法研究

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GPS (Global Positioning System) have high position and velocity precision, star sensor is a high accuracy attitude measurement system, SINS (Strapdown Inertial Navigation System) can get all navigation information precisely at short period. In order to realize high-precision navigation, according to analyze the error model of above systems, both of the state equations and measurement equations were studied. Decentralized Fusion method was used in navigation information processing in which Kalman Filter was used as Local-Estimator, and a new kind of Federated Filter based on partial information fusion was proposed. One of the filter configuration was been selected in the integrated navigation system. The results of the simulation validate that the navigation accuracy can be improved to a higher level in this method.
机译:GPS(全球定位系统)具有很高的位置和速度精度,星形传感器是一种高精度的姿态测量系统,SINS(捷联惯性导航系统)可以在短时间内精确获取所有导航信息。为了实现高精度导航,在分析上述系统的误差模型的基础上,研究了状态方程和测量方程。在以卡尔曼滤波为局部估计器的导航信息处理中,采用了分散融合方法,提出了一种基于局部信息融合的新型联合滤波器。在集成导航系统中选择了一种过滤器配置。仿真结果验证了该方法可以将导航精度提高到更高的水平。

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