This work considers the problem of localization in low-cost, wireless sensor networks. Localization refers to the process by which the nodes in a sensor network discover their geographical location. In a typical sensor network only a few nodes know their position a priori. Thus, I am researching localization algorithms by which the unknown nodes in the network can calculate their positions using information from the known nodes. A good localization solution has the following requirements. First, it must be scalable and distributed. Second, a solution has to be tolerant to errors in the distance measurement. (Errors will be present in the distance measurements due to the difficulty of accurately measuring distance in environments with multi-path reflections.) Third, the solution must converge to accurate location estimates in many different and time-varying environments with constrained communication and computation resources. In other words, a robust solution is required.
The overall goal of this project is to research and evaluate several existing localization algorithms, then extend these algorithms to increase their robustness and incorporate features such as current error estimation, early termination when error bounds are low, and better convergence guarantees.