  Accurate localization and perception are pivotal for enhancing the safety and
reliability of vehicles. However, current localization methods suffer from
reduced accuracy when the line-of-sight (LOS) path is obstructed, or a
combination of reflections and scatterings is present. In this paper, we
present an integrated localization and sensing method that delivers superior
performance in complex environments while being computationally efficient. Our
method uniformly leverages various types of multipath components (MPCs) through
the lens of random finite sets (RFSs), encompassing reflections, scatterings,
and their combinations. This advancement eliminates the need for the multipath
identification step and streamlines the filtering process by removing the
necessity for distinct filters for different multipath types, a requirement
that was critical in previous research. The simulation results demonstrate the
superior performance of our method in both robustness and effectiveness,
particularly in complex environments where the LOS MPC is obscured and in
situations involving clutter and missed detection of MPC measurements.
