On Localization Accuracy in Urban Environments Using TDOA Measurements

This paper investigates the localization accuracy in an urban environments using time-difference-of-arrival (TDOA) measurements. The Cramér-Rao bound (CRB) is derived in order to predict the best achievable localization accuracy by considering the shortest signal paths. The measurement accuracy is modeled depending on the signal path lengths between source and sensors. Simulations demonstrate that the maximum likelihood estimator (MLE) attains the CRB and show its superior accuracy compared to a free-field scenario assumption. Finally, the match between predicted and actual performance is validated using data collected through field measurements in an urban environment.