Cooperative mmWave PHD-SLAM with Moving Scatterers

Paper in proceeding, 2022

Simultaneous localization and mapping (SLAM) using multipath at mmWave frequencies can provide accurate localization in the presence of static landmarks. When radio signals reflected from moving vehicle scatterers (VSs) are observed, the standard SLAM filters exhibit a degraded performance. To address this problem, we propose a probability hypothesis density (PHD)-based SLAM filter, where separate maps are maintained for VS and other types of landmarks. Through a combination of developed (i) local PHD-SLAM and (ii) global map fusion, we demonstrate that the proposed filter can handle the problem.