This paper addresses the problem of distributed recursive filtering for state-saturated systems in a networked communication environment. An output mask function is employed to safeguard the pri- vacy of interaction data during node exchange in sensor networks. Scaled uniform quantization is intro- duced to facilitate the digital communication and optimize the network resource usage. The primary objective of the study is to design a distributed recursive filter that ensures the filtering error covariance remains bounded over a finite horizon. Specifically, by using Riccati-like equations, an upper bound for the filtering error covariance is derived, which depends on the network topology, the output mask func- tion, and the quantization level. The desired gain matrix is then solved recursively. Finally, the effective- ness of the proposed filtering algorithm is demonstrated through a three-tank simulation example.
- Open Access
- Article
- Youyin Hu,
- Chen Zhang,
- Shuai Liu *
Author Information
Received: 16 Feb 2025 | Accepted: 04 May 2025 | Published: 30 Jun 2025
Abstract
Keywords
Distributed filtering | recursive filtering | privacy protection | uniform quantization | output mask
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