Demonstration of Spider‐Eyes‐Like Intelligent Antennas for Dynamically Perceiving Incoming Waves

Abstract

Obtaining a full view and complete information of the surrounding dynamics is of great significance for a plethora of applications in sensing, imaging, navigation, and orientation. However, conventional spatial spectrum methods heavily rely on a priori knowledge with a trial‐and‐error solution fashion, leading to a great challenge to estimate complete information in volatile scenarios. Inspired by the mechanism of the jumping spider (Salticidae), here a universal detection approach driven by an intelligent antenna array, with the usage of amplitude‐only information as inputs, is introduced. The applied machine learning method can process the received time‐varying signals in one single feed‐forward computation, bypassing a heavy recline on prior knowledge of the array structure. As a demonstration, a compact eight‐port antenna array is designed for simultaneous attainments of frequency, direction of arrival, and polarization, covering the entire microwave X band. Both the simulated and experimental results show that the average accuracies for the azimuth angle, elevation angle, and polarization are up to 98%, with a millisecond detection time. Different from conventional methods, the strategy herein does not involve a complex beamforming network and a time‐consuming trial‐and‐error solution fashion, allowing a big step toward a miniaturized, integrated, and cost‐effective detector.

Dynamic recognition and mirage using neuro-metamaterials

“…A rabbit plays freely in front of the neuro-metamaterials under the illumination of a transverse electric plane wave, where the electric field is along the z axis. Meanwhile, three detectors (small monopole antennas) are connected to a series of miscellaneous components to perceive the EM strength (the amplitude of the electric field) at the output plane 37 ; see Methods and Supplementary Note 4 . Note that here all the electronic components are used only to illustrate the perception results for users utilizing microwave frequencies, whereas in visible frequencies the results can be seen with the naked eye.…”

“…A high-directivity lens antenna centered at the neuro- metamaterials was used as the excitation source. Three monopole probes, which we built ourselves, were connected to one RF switch (HMC641ALC4), collecting the amplitude signals from the three ports at microseconds 37 . The received signal was amplified by a broadband amplifier and down-converted by 6 GHz.…”

In Situ Customized Illusion Enabled by Global Metasurface Reconstruction

“…As schematically illustrated in Figure a, we guided the intelligent metasurfaces to generate illusive scattered waves, causing an observer to mistake them for another object, for example, a crocodile. To build a set of intelligent EM system, we made an intelligent EM detector composed of an 8‐port metasurface array for the simultaneous attainment of frequency, direction‐of‐arrival and polarization, covering the entire X‐band [ 40 ] (Supplementary Note 8). In conjunction with this EM detector, we can output the metasurface pattern in real time for an arbitrary illusive scattering requirement.…”

Intelligent metaphotonics empowered by machine learning

“…As an example, the spider-eye-like antenna demonstrated in Ref. [181] is supplemented by a generalised regression neural network [202] to analyze the incoming waves (see Fig. 7(a)).…”

“…ANN in this case explicitly imitates the work of a biological neural network, realizing a system similar to a vision system of a spider. (Adopted from Ref [181]…”