A Novel Positioning System Based on Coverage Area Pruning in Wireless Sensor Networks

Area of Science:

• Wireless Sensor Networks
• Environmental Monitoring
• Localization Algorithms

Background:

• Wireless sensor networks (WSNs) are vital for environmental monitoring, but accurate event localization remains challenging.
• Existing positioning technologies often demand high computational power or specialized hardware, unsuitable for resource-constrained WSNs.
• The need for efficient and accurate localization in WSNs drives the development of new algorithms.

Purpose of the Study:

• To propose a novel range-free positioning algorithm, the Coverage Area Pruning Positioning System (CAPPS), for WSNs.
• To enhance the accuracy of target localization in WSNs without requiring specialized hardware or high computational capabilities.
• To evaluate the performance of CAPPS under practical scenarios, including radio coverage variations.

Main Methods:

• CAPPS determines an approximate target area using sensors that detect the event.
• It then refines this area by utilizing sensors that do not detect the event, effectively pruning the search space.
• A heuristic mechanism and centroid point approach are employed to mitigate positioning errors in dynamic radio environments.

Main Results:

• CAPPS achieved significantly smaller positioning areas compared to Distance Vector Hop (98% smaller), Angle of Arrival (97% smaller), and Received Signal Strength Indicator (93% smaller).
• The proposed centroid point mechanism reduced the probability of excluding the target from 50%–95% to 10%–30% in radio variation scenarios.
• Simulations demonstrated CAPPS's effectiveness in improving localization accuracy and reducing false positioning probabilities.

Conclusions:

• CAPPS offers a highly accurate and efficient range-free localization solution for wireless sensor networks.
• The algorithm is well-suited for resource-constrained WSNs commonly used in environmental monitoring.
• CAPPS demonstrates superior performance over existing methods, particularly in challenging radio environments.