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摘要: 设计了一种分布式扩展卡尔曼滤波器(Extended Kalman filter, EKF), 对非线性目标状态进行估计.在设计过程中, 对滤波误差上界进行优化, 获得了最优滤波增益.此外, 在通信过程中, 考虑恶意攻击信号的同时引入了分布式事件触发机制, 使得系统在保持一定的估计精度的情况下节省通信资源.最后, 以室内的机器人定位问题为例, 验证了提出的滤波器的有效性.Abstract: A distributed extended Kalman filter (EKF) is designed to estimate the nonlinear target state. In the design process, the optimal filtering gain is obtained by optimizing the upper bound of error covariance. In the process of communication, the distributed event-trigger mechanism is introduced meanwhile the malicious attack signal is considered, so that the system can save the communication resources in the case of maintaining certain estimation accuracy. Finally, an indoor robot localization problem is used to verify the effectiveness of the proposed method.
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Key words:
- Distributed event-trigger /
- extended Kalman filtering (EKF) /
- state estimation /
- malicious attacks
1) 本文责任编委 张军平 -
表 1 不同$\bar{\pmb{\vartheta}}_{i, k}$对应的RMSE
Table 1 RMSE corresponding to different $\bar{\pmb{\vartheta}}_{i, k}$
$\bar{\pmb{\vartheta}}_{i, k}$ 5 7 9 11 13 15 RMSE 0.2 0.25 1.38 8.75 15.59 — -
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