A Passive Tracking System Based on Geometric Constraints in Adaptive Wireless Sensor Networks

Area of Science:

• Computer Science
• Electrical Engineering
• Signal Processing

Background:

• Wireless sensor networks (WSNs) offer active and passive tracking schemes.
• Passive tracking, or device-free target tracking, is a promising research area.
• Existing methods often require targets to carry cooperative devices, limiting passive tracking applications.

Purpose of the Study:

• To propose a novel passive tracking scheme for device-free targets in WSNs.
• To enhance energy conservation in WSNs while maintaining tracking accuracy.
• To enable tracking of both single and multiple targets.

Main Methods:

• Exploiting radio frequency tomography (RFT) on line-of-sight links (LOSLs).
• Utilizing adaptive-networking LOSL webs and geometric constraint methodology.
• Investigating spatial diversity techniques for RFT detection.
• Analyzing WSN power consumption and proposing an adaptive networking scheme.

Main Results:

• The proposed scheme adaptively adjusts networking levels to save energy.
• Reduced power consumption was observed without compromising tracking performance.
• Computer simulations validated the effectiveness of the adaptive networking strategy.

Conclusions:

• The developed passive tracking scheme effectively conserves energy in WSNs.
• The method provides qualified tracking performance for device-free targets.
• Adaptive networking is key to balancing energy efficiency and tracking accuracy.