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

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.