Conference paper Open Access

Study of Reflection-Loss-Based Material Identification from Common Building Surfaces

Geng, Yi; Yajnanarayana, Vijaya; Behravan, Ali; Dahlman, Erik; Shrestha, Deep

Perceiving and recognizing material properties of surfaces and objects are fundamental aspects of new and emerging use cases such as robotic perception, virtual reality (VR) applications, digital twins, and creating a 3D digital map of an environment. In this paper, we present results from our simulation-based study of reflection-loss-based material identification from eight common building materials. The study focuses on 2.6 GHz, 28 GHz, and 60 GHz radio carrier frequencies. Analysis of simulation results indicates that a combination of incident angle and reflection loss can be used to properly identify the common building materials. We, therefore, propose a novel joint communication and sensing method for material recognition using reflection loss of the radio signal by the scatterers around the propagation path in a wireless communication network. Compared to existing material identification methods, the proposed reflection-loss-based method is capable of identifying materials from a significant distance without requiring any contact with the object and without requiring dedicated sensors from the infrastructure point of view.

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