Improving Localization Accuracy under Constrained Regions in Wireless Sensor Networks through Geometry Optimization

Area of Science:

• Computer Science
• Electrical Engineering
• Network Engineering

Background:

• Wireless Sensor Networks (WSNs) rely on accurate localization for various applications.
• Existing sensor placement strategies often overlook deployment region constraints.
• Improving localization accuracy is crucial for WSN efficiency and reliability.

Purpose of the Study:

• To propose optimal range-based sensor geometries for wireless sensor networks (WSNs) under specific constraints.
• To enhance target localization accuracy by considering factors like terrain, communication, and security.
• To develop a novel approach for sensor geometry optimization in constrained deployment regions.

Main Methods:

• Modeling the geometry optimization problem as a constrained optimization problem.
• Utilizing D-optimality criterion (maximizing the determinant of the Fisher Information Matrix) as the objective function.
• Transforming the constrained problem using maximum feasible angle and separation angle for analysis.

Main Results:

• Optimal sensor geometries were determined for circular deployment regions with minimum safety distance constraints.
• The study identified relationships between minimum safety distance and maximum feasible angle for optimal configurations.
• The proposed method was extended to arbitrary numbers of sensors and irregular feasible regions.

Conclusions:

• The proposed sensor geometries significantly improve localization accuracy in WSNs.
• The D-optimality-based approach provides an effective framework for constrained sensor placement.
• This research offers practical insights for designing efficient and secure WSNs.