  In this work, we develop a multipath-based simultaneous localization and
mapping (SLAM) method that can directly be applied to received radio signals.
In existing multipath-based SLAM approaches, a channel estimator is used as a
preprocessing stage that reduces data flow and computational complexity by
extracting features related to multipath components (MPCs). We aim to avoid any
preprocessing stage that may lead to a loss of relevant information. The
presented method relies on a new statistical model for the data generation
process of the received radio signal that can be represented by a factor graph.
This factor graph is the starting point for the development of an efficient
belief propagation (BP) method for multipath-based SLAM that directly uses
received radio signals as measurements. Simulation results in a realistic
scenario with a single-input single-output (SISO) channel demonstrate that the
proposed direct method for radio-based SLAM outperforms state-of-the-art
methods that rely on a channel estimator.
