On the Use of Mpc Amplitude Information in Radio Signal Based Slam

In this paper we present a Bayesian framework for utilizing the amplitude information of multipath components (MPCs) in radio-signal-based simultaneous localization and mapping (SLAM). The developed algorithm exploits the complex amplitudes of MPC parameters that are provided by the radio channel parameter estimator. With this information, the algorithm can adapt the probabilities of detecting features within a radio signal in a time-variant way. The algorithm increases the life-time of used features and it better explores “weak” MPCs, i.e., MPCs with low signal-to-interference-plus-noise-ratios (SINRs) in dense multipath.