Energy-Efficient Distributed Filtering in Sensor Networks: A Unified Switched System Approach

Area of Science:

• Control Systems Engineering
• Signal Processing
• Networked Systems

Background:

• Sensor networks require energy-efficient data processing due to power constraints.
• Distributed filtering is crucial for analyzing data from multiple sensors.
• Nonuniform sampling and data reduction techniques are common in sensor networks.

Purpose of the Study:

• To develop an energy-efficient distributed filtering method for sensor networks.
• To propose a unified switched system approach to model complex phenomena.
• To ensure exponential stability and H∞ performance for the filtering error system.

Main Methods:

• A unified switched system model is developed to incorporate nonuniform sampling, data reduction, quantization, and missing measurements.
• Sufficient conditions for exponential stability in the mean-square sense are derived.
• H∞ performance is analyzed for the filtering error system.

Main Results:

• The proposed unified model effectively captures various signal processing and transmission challenges.
• Sufficient conditions guarantee the exponential stability of the filtering error system.
• The H∞ performance level is prescribed and achieved.

Conclusions:

• The unified switched system approach provides an effective framework for energy-efficient distributed filtering.
• The design technique is validated through simulation and experimental studies.
• The method offers a robust solution for power-constrained sensor network applications.