Graph-based Simultaneous Localization and Bias Tracking for Robust Positioning in Obstructed LOS Situations

We present a factor graph formulation and particle-based sum-product algorithm for robust localization and tracking in multipath-prone environments. The proposed sequential algorithm jointly estimates the mobile agent's position together with a time-varying number of multipath components (MPCs). The MPCs are represented by “delay biases” corresponding to the offset between line-of-sight (LOS) component delay and the respective delays of all detectable MPCs. The delay biases of the MPCs capture the geometric features of the propagation environment with respect to the mobile agent. Therefore, they can provide position-related information contained in the MPCs without explicitly building a map of the environment. We demonstrate that the position-related information enables the algorithm to correctly infer the agent position even in fully obstructed LOS situations. In a challenging scenario we demonstrate the presented algorithm to significantly outperform state-of-the-art multipath-aided tracking algorithms and show that the performance of our algorithm attains the posterior Cramér-Rao lower bound (PCRLB).