Robotic near-field sensing and localization technology with deep integration of channel information and mobile trajectories

With the booming development of the intelligent robot industry, integrating both communication and sensing functions into communication devices has become an important development trend in the future. To achieve high-precision sensing in communication devices, utilizing device mobility to form large-scale virtual antenna arrays becomes a promising solution. However, the existing sensing system utilizing communication devices mobility is designed based on the assumption of a far-field channel, which can only provide angle of arrival (AoA) localization information. It cannot directly provide distance estimation and requires multiple access points (APs). To address this problem, this paper develops a new near-field sensing architecture for mobile robots by fusing multi-antenna channel state information (CSI) and the robot's motion trajectory, which can realize high-precision localization with only a single AP. Specifically, a joint AoA-distance parameter estimation scheme is proposed, which corrects the phase offset by coupling the CSI of two antennas. Secondly, it is theoretically demonstrated that the scheme with multiple antenna CSI coupling can achieve high-precision localization under near-field conditions in both linear and curved trajectories. Further, a cluster-weighted multi-scale estimation scheme is proposed to separate the line-of-sight paths accurately. Finally, a prototype experimental validation system based on a mobile robot and commercial WiFi is constructed. The experimental results show that the proposed system can work in complex environments and its localization accuracy is better than the existing schemes.