Low complexity least-square estimator for RSS-based localization in Wireless Sensor Networks

• Published in: 2012 International Conference on Communications and Information Technology (ICCIT) pp. 331 - 335
• Main Authors: Alhasant, A. I., Sharif, B. S., Tsimenidis, C. C., Neasham, J. A.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-06-2012
• Subjects: Biological system modeling; Computational complexity; Computational modeling; Least squares approximation; Maximum likelihood estimation; Wireless sensor networks
• DOI: 10.1109/ICCITechnol.2012.6285818
• ISBN: 9781467319492; 146731949X

This paper presents an efficient Received Signal Strength RSS-based localization approach utilizing a Tree Search Algorithm (TSA). In comparison to the existing exhaustive search algorithms, e.g. Least Square Estimators (LSE) and Error Controlling localization (Ecolocation), the proposed approach achieves considerable reduction in computational complexity and storage requirements. The effectiveness of the TSA is evaluated through simulation and real experiments. The presented results show that the performance of the new approach closely achieves LSE and performs better than Ecolocation algorithms. Moreover, at a comparable system complexities, TSA outperforms the simplistic Proximity and Centroid localization algorithms.