In this paper, we present a Swin Transformer based indoor localization framework that employs RF hologram tensors to locate multiple ultra-high frequency (UHF) passive Radiofrequency identification (RFID) tags. The RF hologram tensor captures the strong relationship between RFID measurements and spatial location, and helps to improve the robustness of the system in dynamic environments. We develop a Swin Transformer-based hologram filter network to clean the fake peaks in hologram tensors caused by multipath propagation and phase wrapping, exploring the spatial relationship between tags. In contrast to fingerprinting-based localization systems that use deep networks as classifier, the proposed network treats localization as a regression problem. An intuitive peak finding algorithm is introduced for location estimation using the sanitized hologram tensors. We prototype the proposed system using commodity RFID devices and conduct extensive experiments to evaluate its performance.
Locating Multiple RFID Tags with Swin Transformer-based RF Hologram Tensor Filtering
2022-09-01
365400 byte
Conference paper
Electronic Resource
English