Highly Integrated Dual‐Modality Microwave Frequency Identification System. Issue 10 (19th July 2022) - Yao, Yuhan; Zhao, Yuhe; Wei, Yanxian; Zhou, Feng; Chen, Daigao; Zhang, Yuguang; Xiao, Xi; Li, Ming; Dong, Jianji; Yu, Shaohua; Zhang, Xinliang
Abstract: Photonic‐assisted microwave frequency identification systems have been extensively explored and widely applied for civil and defense applications. Full integration of this system is a promising candidate in attempts to meet the requirements of reduction in size, weight, and power. Although many integrated photonic chips have been reported in different technologies, none has monolithically integrated all the main active and passive optoelectronic components. Furthermore, previous approaches could identify either a single frequency signal instantaneously or multiple frequency signals statistically, but not both, hindering the practical applications. Here, a highly integrated dual‐modality microwave frequency identification system on a single chip is reported. All critical components including a modulator, a sweeping‐frequency filter, a frequency‐selected filter, an amplitude comparison function, and parallel photodetectors, are monolithically integrated on the silicon‐on‐insulator platform. Thanks to the dual‐modality scheme, the chip is able to identify different types of microwave signals, including single‐frequency, multiple‐frequency, chirped, and frequency‐hopping microwave signals, as well as discriminate instantaneous frequency variation among the frequency‐modulated signals. This demonstration exhibits a highly integrated solution and fully functional microwave frequency identification, which can meet the requirements in reduction of size, weight, and power for future advanced microwave photonic processor. Abstract : Precisely detecting and measuring the frequency of unknown microwave signals are essential to myriad civil and defense applications. Here, a highly integrated dual‐modality microwave frequency identification system is demonstrated, which can identify different types of microwave signals and discriminate instantaneous frequency variation. It promotes the applications of miniature on‐chip microwave photonics systems with low size, weight, and power consumption.