Characterizing and improving the collaborative position location problem

Indoor positioning has become a hot research topic due to a plethora of interesting applications ranging from emergency responder tracking to location-based services. In this work we focus on the problem of network localization, sometimes called collaborative localization, where a network of nodes is to be localized using both connections to anchors (when they exist) and connections between unlocalized nodes [1]. The fast and efficient IPPM algorithm developed in [2] and [3] performs well in most situations. However, it suffers from the existence of local, non-global minima which cause large localization error. In this work, we propose a technique for identifying and mitigating local minima errors, and we show that collaborative position location estimates can be greatly improved using our method.