Distributed RSS-Based Localization in Wireless Sensor Networks Based on Second-Order Cone Programming

Sensors

Slavisa Tomic²  Marko Beko¹ 

[1] Universidade Lusófona de Humanidades e Tecnologias, Campo Grande 376, Lisboa 1749-024, Portugal; E-Mail:;Institute for Systems and Robotics (ISR), Instituto Superior Técnico (IST), Av. Rovisco Pais 1, Lisbon 1049-001, Portugal

关键词: wireless localization;    wireless sensor network (WSN);    received signal strength (RSS);    second-order cone programming (SOCP) problem;    cooperative localization;    distributed localization;   

DOI  :  10.3390/s141018410

来源: mdpi

【 摘 要 】

In this paper, we propose a new approach based on convex optimization to address the received signal strength (RSS)-based cooperative localization problem in wireless sensor networks (WSNs). By using iterative procedures and measurements between two adjacent nodes in the network exclusively, each target node determines its own position locally. The localization problem is formulated using the maximum likelihood (ML) criterion, since ML-based solutions have the property of being asymptotically efficient. To overcome the non-convexity of the ML optimization problem, we employ the appropriate convex relaxation technique leading to second-order cone programming (SOCP). Additionally, a simple heuristic approach for improving the convergence of the proposed scheme for the case when the transmit power is known is introduced. Furthermore, we provide details about the computational complexity and energy consumption of the considered approaches. Our simulation results show that the proposed approach outperforms the existing ones in terms of the estimation accuracy for more than 1.5 m. Moreover, the new approach requires a lower number of iterations to converge, and consequently, it is likely to preserve energy in all presented scenarios, in comparison to the state-of-the-art approaches.

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland.