Vehicles need to locate other vehicles and network infrastructure elements on unmanned autonomous vehicle (UAV) systems. Human passengers also need to locate and be located by the vehicles, preferentially using a portable device, such as a smartphone. This paper analyses the accuracy of several localization algorithms in the remote location of entities running WiFi access points, using measurements collected in moving vehicles using a new application developed by us. The algorithms analysed include closed form estimators and one based on second order cone programming (SOCP) relaxation, which exhibits the best accuracy and is capable of estimating the path loss exponent and the transmission power. Although, due its lower complexity, the Levenberg-Marquardt algorithm was better suited for the stand-alone Android prototype application. The results show that real-time accurate positioning of static/slow moving remote entities is possible, even though the accuracy degrades when the measuring vehicle’s speed increases.