A group of researchers from the University of California at Santa Barbara developed methods for determining the contours of fixed objects behind a wall by analyzing the distortion of the Wi-Fi signal. This new method, called WiffRact, is based on the changes in the Wi-Fi signal caused by the interaction of electromagnetic waves with the edges of objects.
The researchers utilized the geometric theory of diffraction (GTD) to develop their mathematical approach. The GTD theory describes the behavior of electromagnetic waves when encountering obstacles. It introduces the concept of diffracted waves, which occur when a wave interacts with a rib or sharp peak on the surface of an object. When a wave encounters a rib, diffracted waves form a rotation cone known as a KELLER cone, with an opening angle that is double the angle between the falling wave and the tangent. If the wave falls perpendicularly on the tangent, the cone becomes a plane, and if it falls on the tip of the object, the diffracted waves diverge in all directions evenly.
The proposed method does not require preliminary training in a neural network and is not limited to recognizing specific objects learned through machine learning. Instead, the method aims to recreate the contours of any objects by tracking their edges. The signal analyzer, which simulates an