Pedestrians are particularly vulnerable traffic participants with a very high fatality rate. An important component of Advanced Driver Assistant Systems is the accurate localization of pedestrians and other vulnerable traffic participants using various sensors and other technologies. Localization using radio frequency (RF) signals is commonly used, because of the widespread availability of wireless radios, ease of deployment, and the fact that RF-based ranging will work in all weather and light conditions. However, the accuracy of RF-based ranging in vehicular networks is easily affected by high device dynamics and mobility, leading to varying impacts of shadowing and multipath fading. In this paper, we introduce a new ranging algorithm that first uses a novel filtering scheme that reduces the impact of mutipath fading and shadowing. Then, we use an exhaustive search method to minimize an MSE function that represents the difference between the filtered RSSI values and the expected RSSI values (based on the channel model) to estimate the distance between transmitter and receiver. The performance of the proposed ranging algorithm is evaluated using real field measurements in terms of accuracy and convergence time.
