Detection of wheelchairs in indoor and public spaces using an LTE-based passive radar

This study explores the potential of leveraging Long Term Evolution (LTE) as an illuminator of opportunity, combined with Machine Learning (ML), to detect the presence of objects in the nearby environment. Specifically, the research focuses on detecting wheelchairs. The machine learning algorithm is trained on datasets generated from the Master Information Block (MIB) and Signal Information Block 1 (SIB1). The data was collected using a software-defined radio (SDR) tuned to LTE band 3. The experimental results showed that an LTE-based passive SDR system can detect the presence of a wheelchair as well as other large objects within a room with a high degree of accuracy.