Probabilistic Estimation of Location Error 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 method in which nodes estimate the amount of error present in their derived positions with a certain probability. A linear scaling function is applied to the the calculated theoretical lower bound on localization variance, given by the Cramér-Rao Lower Bound (CRLB), so that it closely matches the variance of a given localization system. Probabilistic methods then use this variance function to estimate localization error. Coefficients for the scaling function were derived through simulations, and the proposed method was used to successfully estimate localization error in a multitude of randomly generated network topologies. Once known, estimates can be integrated into location dependent schemes to improve on their robustness to localization error.