When a radio wave encounters a building in its path, it doesn't just reflect or get absorbed: it bends around it, much like ocean waves flowing around a rock, leaving calm water behind. In radiophysics, this phenomenon creates a radio shadow — a complex pattern of zones where the signal is amplified or attenuated, which scientists call a radio portrait. In this pattern, like in an Impressionist painting, information about the obstacle's shape, size, and distance is encoded. The idea itself isn't new: back in the 17th century, Christiaan Huygens proposed that every point on a wavefront becomes a source of secondary waves, and a century later, Joseph von Fraunhofer mathematically described how these waves interfere in the far field, creating characteristic patterns. The researchers combined these principles for the radio range and built a model that 'develops' the radio portrait by reading data with precision available at ordinary Wi-Fi and cellular frequencies: that is, without complex equipment, simply by analyzing signal patterns. A striking fact: the method hits not a technical limit but a fundamental physical limit — the Cramér–Rao bound, which mathematically forbids extracting more information from a signal than its statistical nature allows. In other words, radio portraits are as sharp as physically possible in our world, and further improvement would require violating the laws of physics. This painting analogy, of course, simplifies: in reality, the model works with multidimensional data and accounts for polarization, but the essence remains — radio waves paint us accurate portraits of the invisible.