Localization Methods based on Error Analysis and Modeling in Two Dimensions

Wireless sensor networks (WSNs) have shown promise in a broad range of applications. One of the primary challenges in leveraging them lies in gathering accurate position information for the deployed sensors while minimizing power cost. Through analyzing the error associated with acquiring such position information, we developed several novel localization methods based on modeling the analyzed error and applying rigorous mathematical and statistical principles to produce improved location estimates compared with existing methods. The methods presented herein have been utilized for a two-dimensional space, which provides for many real-world applications. These methods utilize only two mobile beacons that can be mounted to a vehicle, rather than a costly, large array. The primary measurement taken to perform localizations is received signal strength (RSS). Unlike many previously existing methods, the techniques presented herein utilize practical, realistic assumptions and were progressively designed to mitigate incrementally discovered limitations. To exercise and analyze the developed methods, a multiple-layered simulation environment was developed in tandem. The approach, developed methodologies, and software infrastructure presented herein provide a framework for future endeavors within the field of wireless sensor networks.