Gestion de la localisation dans les réseaux de capteurs sans fil

Abstract

This Master’s thesis focuses on improving localization accuracy in Wireless Sensor Networks (WSNs), a critical challenge for many applications with strict energy and environmental constraints. We propose an innovative hybrid approach combining the DV-Hop algorithm, Particle Swarm Optimization (PSO), and regression-based correction. This method relies on a progressive integration of localization and optimization techniques to refine node position estimates. A systematic evaluation implemented in MATLAB, based on variations in the number of nodes, communication range, and anchor ratio, demonstrates that our approach outperforms DV-Hop and RSSI methods in terms of accuracy, robustness, and energy efficiency, while remaining suitable for the constrained environments of WSNs.