Radio Simultaneous Localization and Mapping with Moving Object Tracking in Dynamic Environments

Generation (5G) mobile communication provides high-resolution measurements of delays and angles, which make radio simultaneous localization and mapping (SLAM) a possibility. Current radio SLAM systems focus on static environments. However, moving objects may degrade the performance of SLAM systems. In this paper, we propose an integrated radio SLAM and moving object tracking scheme for dynamic environments. Specifically, we first use a grid-based object detection method to detect and filter out measurements belonging to the multipath components (MPCs) of moving objects for accurate radio SLAM. After obtaining the precise vehicle position via SLAM, a curve fitting method is used to track and predict the trajectories of the moving objects, and the prediction results will help in the detection of the object at the next moment. Finally, simulation results demonstrate the performance of the proposed scheme.