Location error estimation in wireless ad hoc networks

Many ad hoc network applications rely on nodes having accurate knowledge of their geographic locations. However, inherent in all localization systems is a degree of error in computed positions, which can compromise the accuracy and efficiency of location dependent applications and protocols. We propose a scheme in which nodes estimate the amount of error present in their derived positions with a certain probability. Localization error variance is modeled with a function based on the calculated theoretical lower bound on estimator variance, given by the Cramér–Rao Lower Bound (CRLB). Probabilistic methods then use this variance model to estimate upper bounds on localization error, which are computed locally by wireless devices. Best fits between the model and the actual location error variance using both time of arrival (TOA) and received signal strength (RSS) distance measurements were determined by a least squares estimator over repeated localization simulations. The proposed method was used to accurately estimate location error at given probabilities in a multitude of randomly generated network topologies within ±10% of the actual localization error. Once known, estimates can be integrated into location dependent schemes to improve on their robustness to localization error.