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Distributed Consensus Cubature Information fusion in Saturated Inertial Sensors Network

机译:饱和惯性传感器网络中的分布式共识立方信息融合

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In this paper, we propose a new approach of consensus-based Cubature Kalman filtering problem for a inertial sensor networks with gyroscopes and accelerometers saturations. The communication path is represented by a connected indirect graph between nodes and sensors. Saturation phenomenon exists both in the state and in the measurement. A comparison between CKF and UKF based consensus on Information is carried out. The Consensus approach is developed to estimate the true state of the target following a state equation with saturation function. Finally, the superiority of the CKF based consensus versus the previously proposed consensus-based unscented Kalman filtering is demonstrated through multiple simulations scenarios.
机译:在本文中,我们提出了一种具有陀螺仪和加速度计饱和度的惯性传感器网络的基于共识的Comature Kalman滤波问题的新方法。 通信路径由节点和传感器之间的连接间接图表示。 饱和现象在状态和测量中都存在。 执行CKF与UKF基于信息的比较。 开发了共识方法以估计具有饱和函数的状态方程之后的目标的真实状态。 最后,基于CKF的共识与先前提出的基于共识的无名Kalman滤波的优势通过多个模拟方案进行了说明。

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