Performance enhancement of microwave photonic-filter-based interrogation system using machine-learning algorithm
Real-time Photonic Measurements, Data Management, and Processing VI(2021)
摘要
Microwave photonic filter (MPF) based interrogation solutions have attracted considerable research interest, through the sensing information conversion from the optical domain to the microwave domain and high-resolution electrical spectrum analyzing processing techniques. In order to overcome the trade-off between measurement accuracy and interrogation speed existing in the traditional direct-detection method, an efficient machine learning algorithm is introduced into the MPF-based interrogation system. Compared with the traditional direct-detection method, the proposed method can achieve better measurement accuracy under the sparsely sampled frequency response, whilst the interrogation speed is greatly improved. In addition, the well-trained model has strong adaptability to the amplitude variation of the microwave photonic filtering response.
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关键词
interrogation system,microwave,machine-learning machine-learning,photonic-filter-based
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