In this paper, we propose a radio-based passive target tracking algorithm using multipath measurements, including the angle of arrival and relative distance. We focus on a scenario in which a mobile receiver continuously receives radio signals from a transmitter located at an unknown position. The receiver utilizes multipath measurements extracted from the received signal to jointly localize the transmitter and the scatterers over time, with scatterers comprising a moving target and stationary objects that can reflect signals within the environment. We develop a comprehensive probabilistic model for the target tracking problem, incorporating the localization of the transmitter and scatterers, the identification of false alarms and missed detections in the measurements, and the association between scatterers and measurements. We employ a belief propagation approach to compute the posterior distributions of the positions of the scatterers and the transmitter. Additionally, we introduce a particle implementation for the belief propagation method. Simulation results demonstrate that our proposed algorithm outperforms existing benchmark methods in terms of target tracking accuracy.