论文标题
基于ADMM的分布式加权最小二乘估计器
Distributed Weighted Least Squares Estimator Based on ADMM
论文作者
论文摘要
无线传感器网络最近由于其广泛的适用性和易于安装而受到了很多关注。本文与分布式状态估计问题有关，其中所有传感器节点都需要达成共识估计。加权最小二乘（WLS）估计器是解决此问题的一种吸引人的方法，因为它不需要任何先前的分发信息。为此，我们首先利用信息过滤器和WLS估计器之间的等效关系。然后，我们在关系下建立了一个优化问题，再加上共识约束。最后，基于共识的分布式WLS问题通过乘数的交替方向方法（ADMM）解决了。数值模拟以及理论分析证明了节点之间的收敛性和共识估计。
Wireless sensor network has recently received much attention due to its broad applicability and ease-of-installation. This paper is concerned with a distributed state estimation problem, where all sensor nodes are required to achieve a consensus estimation. The weighted least squares (WLS) estimator is an appealing way to handle this problem since it does not need any prior distribution information. To this end, we first exploit the equivalent relation between the information filter and WLS estimator. Then, we establish an optimization problem under the relation coupled with a consensus constraint. Finally, the consensus-based distributed WLS problem is tackled by the alternating direction method of multiplier (ADMM). Numerical simulation together with theoretical analysis testify the convergence and consensus estimations between nodes.
