Minimal Number of Sensor Nodes for Distributed Kalman Filtering
Minimal Number of Sensor Nodes for Distributed Kalman Filtering
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DOI：
10.1109/tsmc.2020.3034732
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发表时间：
2022-03
期刊：
影响因子：
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通讯作者：
Wangyan Li;Fuwen Yang;D. Thiel;G. Wei
中科院分区：
文献类型：
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作者：
Wangyan Li;Fuwen Yang;D. Thiel;G. Wei
发现和识别传感器网络中最少数量的传感器节点是实现分布式状态估计器的最基本问题之一。尽管有大量的研究研究传感器网络，他们中的大多数人忽略了这个问题，或假设所考虑的传感器网络来与一个理想的传感器节点数量。我们在本文中重新讨论这个问题。为此，最小数量的传感器节点问题的形式化和一个新的可观测性条件，即最小节点一致可观测性（MNUO），然后提出。其次，应用该模型研究了分布式卡尔曼滤波算法的稳定性问题。在MNUO条件下，给出了保证其稳定性的条件，并得到了选择最小传感器节点数前后滤波性能关系的结果。最后给出了传感器网络中传感器节点数目最少的优化方法和算例。
Finding and identifying the minimal number of sensor nodes for a sensor network is one of the most basic problems for the implementation of distributed state estimators. Despite a plethora of research studied sensor networks, most of them ignored this problem or assumed the considered sensor network comes with an ideal number of sensor nodes. We revisit this problem in the current paper. To this end, the minimal number of sensor nodes problem is first formalized and a novel observability condition, namely, minimal nodes uniform observability (MNUO), is then proposed. Next, this MNUO is applied to study the stability issues of the distributed Kalman filtering algorithm. In what follows, under the condition of MNUO, conditions to ensure its stability are given and the results about the relation of the filtering performance before and after selecting the minimal number of sensor nodes are obtained. Finally, optimization solutions and an example are given to find the minimal number of sensor nodes for a sensor network.