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Research on the multi-sensor information fusion method based on factor graph

机译:基于因子图的多传感器信息融合方法研究

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Aimed at the problem of the time synchronization and the change of different sensors' usability, a multi-sensor information fusion method based on factor graph topology has been proposed combined with the principle of the probability graph model. Different factor nodes represent the state and measurement update process of the system. The topology model of the factor graph has been established according to the real-time measurement information. The recursion and update of the state has been realized by means of choosing the appropriate cost function, which can effectively improve the fusion effect of the multi-sensor information and increase the estimation precision. The simulation results show that the method proposed by the paper has a higher filtering accuracy compared with the traditional method under the condition of the different environment. The performance can satisfy various changing mission and environmental requirements of the vehicle.
机译:针对时间同步和不同传感器可用性变化的问题,结合概率图模型原理,提出了一种基于因子图拓扑的多传感器信息融合方法。不同的因子节点代表系统的状态和度量更新过程。根据实时测量信息建立了因子图的拓扑模型。通过选择合适的代价函数可以实现状态的递归和更新,可以有效地提高多传感器信息的融合效果,提高估计精度。仿真结果表明,在不同环境条件下,本文提出的方法比传统方法具有更高的滤波精度。性能可以满足车辆不断变化的任务和环境要求。

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