In this paper, the recursive distributed filtering problem is investigated for a class of discrete shift-varying two-dimensional systems over sensor networks. To alleviate the resource consumption, a new component-based, node-wise yet dynamic event-triggered scheme is proposed to regulate data transmissions among the neighboring sensor nodes over the sensor-to-filter channels. The aim is to devise a distributed filter to ensure the existence of an upper bound on the filtering error variance and subsequently minimize such a bound at each iteration. In virtue of stochastic analysis techniques and mathematical induction principle, a recursive algorithm is developed to calculate the desired upper bound which is then locally minimized by appropriately parameterizing the filter gains. Furthermore, the effect of the event-triggered scheme on the estimation accuracy is rigorously evaluated. The validity of the established filter design strategy is finally demonstrated by a numerical simulation.

中文翻译：

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传感器网络上二维系统的递归分布式滤波器设计：基于组件、节点和动态事件触发方案

本文研究了传感器网络上一类离散位移变二维系统的递归分布式滤波问题。为了减轻资源消耗，提出了一种新的基于组件的、基于节点的动态事件触发方案来调节相邻传感器节点之间通过传感器到过滤器通道的数据传输。目的是设计一个分布式滤波器，以确保存在滤波误差方差的上限，并随后在每次迭代时最小化这样的边界。凭借随机分析技术和数学归纳原理，开发了一种递归算法来计算所需的上界，然后通过适当地参数化滤波器增益来局部最小化该上界。此外，严格评估事件触发方案对估计精度的影响。最后通过数值模拟证明了所建立的滤波器设计策略的有效性。