Generally, distributed H_∞ filtering approach achieves a certain disturbance attenuation level in the full frequency range. However, the energy of system noise or reference input usually limits in a specified frequency range. To reduce such a design conservatism, this article develops a distributed filtering approach based on dual scale, that is, filtering over a finite-time interval from time scale and also on a specified finite-frequency region from the frequency scale. Our target is to make the filtering error under sensor networks monitoring be relaxed into an ellipsoid bound rather than asymptotically converging to zero for exogenous noise in a specified frequency range. Finally, two illustrative examples demonstrate the strength of the developed filtering approach.

一般地，分布式ħ _∞滤波方法实现了在整个频率范围内某一干扰衰减水平。但是，系统噪声或参考输入的能量通常限制在指定的频率范围内。为了减少这种设计保守性，本文开发了一种基于双重标度的分布式滤波方法，即从时间标度开始在有限时间间隔内进行滤波，并从频率标度开始在指定的有限频率范围内进行滤波。我们的目标是使传感器网络监控下的滤波误差减小到椭圆形范围内，而不是将指定频率范围内的外源噪声渐近收敛到零。最后，两个示例说明了开发的过滤方法的优势。