一种基于数据驱动传输策略的带宽受限的分布式融合估计器

针对无线网络化多传感器融合估计中存在的网络拥堵、传感器能量有限以及通信带宽有限的问题, 本文以多传感器经通信网络组成的线性离散随机系统为研究对象, 提出了一种基于数据驱动传输策略的带宽受限的分布式融合估计器, 能够在降低传感器数据传输率的同时满足有限带宽的限制. 在目标状态满足高斯性的前提下, 给出了融合估计误差均方差一致有界的条件. 最后通过算例仿真验证所提方法的有效性.

A Decentralized Fusion Estimator Using Data-driven Communication Strategy Subject to Bandwidth Constraints

A decentralized fusion estimator using data-driven communication strategy subject to bandwidth constraints is proposed for linear discrete-time stochastic dynamical systems composed of sensors via a communication network, aiming to deal with the network traffic, energy and bandwidth constraints in wireless networked multi-sensor fusion estimation. The estimator can realize a reduced communication rate as well as meet the limitation of bandwidth. The conditions ensuring that the estimation error is uniformly bounded in mean square error are given when the target states are Gaussian. Finally, a simulation example is given to confirm the effectiveness of the proposed approach.