  This paper addresses the challenge of achieving reliable and robust
positioning of a mobile agent, such as a radio device carried by a person, in
scenarios where direct line-of-sight (LOS) links are obstructed or unavailable.
The human body is considered as an extended object that scatters, attenuates
and blocks the radio signals. We propose a novel particle-based sum-product
algorithm (SPA) that fuses active measurements between the agent and anchors
with passive measurements from pairs of anchors reflected off the body. We
first formulate radio signal models for both active and passive measurements.
Then, a joint tracking algorithm that utilizes both active and passive
measurements is developed for the extended object. The algorithm exploits the
probabilistic data association (PDA) for multiple object-related measurements.
The results demonstrate superior accuracy during and after the obstructed
line-of-sight (OLOS) situation, outperforming conventional methods that solely
rely on active measurements. The proposed joint estimation approach
significantly enhances the localization robustness via radio sensing.
