Sensor localization using received signal strength measurements for obstructed wireless sensor networks with noisy channels

This paper proposes a new approach to cope with the challenges in sensor localization in an obstructed environment even in the presence of channel noise. In particular, a progressive localization scheme is proposed that does not necessitate the need for any cluster as most existing schemes do. Initialization is done by generating a quadrilateral of sensor nodes where the connectivity weight between them is computed based on the estimated distance from a reference point, which may be any vertex of the quadrilateral. Distances between sensor nodes are mapped from a path-loss model that is governed by the NLOS and Rayleigh fading models, considering noisy communication channel. With the initial quadrilateral characterized, the other sensor nodes are localized in a progressive manner based on the same mapping model. Errors due to presence of obstacles and noisy channel are reduced by studying the estimated distances contributed from the neighboring sensor nodes. Efficiency of our proposed scheme is measured in terms of total power dissipation for localization and the total degree of neighboring nodes required for error reduction. Apart from simulation experiments, we verify our proposed scheme using real hardware deployment in both indoor and outdoor environments. Results reveal that the proposed scheme improves localization precision substantially.