Distributed and Iterative Processing for Wireless Sensor Networks with Multiple Local Fusion Centres

随着先进的传感器技术和无线通信技术的成熟，无线传感器网络(WSNs)变得越来越流行。一般来说，传感器节点具有感知、计算和通信的能力。因此，传感器网络被广泛应用于军事战场监控。然而，同时，由于大多数传感器节点都是电池供电的，一些功能可能没有得到充分的利用，并受到一定限制。为了克服传感器节点的功率限制，使用多个局部融合中心(LFC)可以有效地允许以分层的方式构建WSN。LFC将从位置较近的传感器节点收集信息。因此，传感器节点可以节省电能。为了共享测量信息以进行更好的估计，WSN中的LFC通过特定的无线Mesh网络连接。在这个拟议的项目中，我们的目标是发展i)局部融合的分布式估计方法；ii)LFC之间的迭代合作通信机制；以及iii)在有约束的情况下优化性能的性能分析。

Wireless sensor networks (WSNs) are becoming popular as wireless sensor nodes are matured with advanced sensor and wireless communication technologies. In general, sensor nodes are capable of sensing, computing, and communicating. Therefore sensor networks are widely used in military battlefield surveillance. However, at the same time, as most sensor nodes are battery-powered, some functions may not be fully utilized and limited by certain constraints. To overcome power constraints of sensor nodes, the use of multiple local fusion centers (LFCs) could be effective, which allows building the WSN in a layered manner. A LFC will collect information from closely located sensor nodes. Thus, sensor nodes can save power. To share measured information for better estimation, the LFCs in a WSN are connected through a certain wireless mesh network. In this proposed project, we aim at developing i) distributed estimation methods at a local fusion; ii) iterative cooperation communication mechanisms between LFCs; and iii) performance analysis to optimize the performance with constraints.