Passive Tags + 3D Radar Enable Privacy-Safe Indoor Localization

A team led by Quanfeng Wang (with Alexander H. Paulus, Mei Song Tong, and Thomas F. Eibert) proposes a novel indoor localization technique that relies on 3-D near-field (NF) passive radar imaging. Instead of using active transmitters or cameras, the method exploits ambient electromagnetic fields already present in indoor environments. Low-cost, passive tags are introduced to boost the scattering field strength, enabling precise localization at the imaging level. The approach is designed to work even in challenging conditions—such as limited bandwidth or highly reflective environments—where traditional methods fail. The passive tags, with distinct geometrical and frequency-varying properties, allow intuitive differentiation between people or objects, while maintaining privacy since no identifiable personal data is captured.

The technique addresses growing concerns over privacy in localization systems. By using passive tags that reflect ambient signals rather than emitting or recording data, the method inherently respects user privacy. The paper discusses additional privacy protection mechanisms, leveraging the frequency-varying characteristics of the tags. Simulation and experimental results confirm the effectiveness of various passive tag designs. The work was published in Progress In Electromagnetics Research (PIER) in 2024 and is now available on arXiv. This approach could enable privacy-friendly indoor navigation for smart buildings, warehouses, hospitals, and emergency services without requiring expensive infrastructure or compromising user data.