UWB SLAM with Rao-Blackwellized Monte Carlo data association

In situations where the environment is filled with dust or smoke, like in many emergency scenarios, it is still possible to sense the surrounding and build maps by using ultra-wideband (UWB) Radar. This can help firemen and other rescue personnel. In this paper, a method to solve the SLAM (simultaneous localization and mapping) problem is presented. Using UWB radar with a bat-type antenna array consisting of two RX antennas and one TX antenna in the middle, features of the surroundings are detected and used as landmarks for navigation. The main challenge of this approach is the problem of data association, i.e. the task of assigning time-of-flight measurements to corresponding landmarks. The solution presented in this article uses a state space model in combination with a Rao-Blackwellized particle filter.