In this study we compare the performance of five least-square based methods for the localization of a target using intensity measurements of randomly placed acoustic sensors. Specifically, we propose a novel quadratic-term elimination (QE) method that gives a closed form least square solution and empirically yields the highest localization accuracy. Applications of this method to the localization and tracking of moving vehicles in a wireless sensor field experiment showed promising results.