基带
计算机科学
公制(单位)
假警报
算法
电子工程
领域(数学)
噪音(视频)
数学
电信
工程类
人工智能
带宽(计算)
运营管理
图像(数学)
纯数学
作者
Yan Yang,Shuguo Xie,Yakai Dong,Tianheng Wang,Xin Zhao
出处
期刊:IEEE Sensors Journal
[Institute of Electrical and Electronics Engineers]
日期:2021-03-22
卷期号:21 (12): 13495-13505
被引量:8
标识
DOI:10.1109/jsen.2021.3068003
摘要
An electric field measurement system with two optical pulse sources down-converts the high-frequency electric signal to the baseband through a probe exploiting the electro optic-effect. From that process, it is feasible to recover the measured frequency. However, the majority of the current studies focus on the case where the difference between the two repetition frequencies is quite small, while only a few involve larger frequency differences. Nevertheless, in a non-laboratory uncontrolled environment such as a field measurement, it is commonly unfeasible to guarantee a small frequency difference imposing further study on frequency recovery methods under larger frequency difference. Spurred by that, in this paper we propose a universal frequency recovery algorithm relying on the Remainder Matching (RM) technique, which is suitable for both large and small frequency differences. In our method, we employ the RM technique to determine the exact remainder combination in the first repetition frequency intervals and calculate the measured frequency. We also present the theoretical basis of RM, along with a summary of the system design rules, which have a significant impact on the performance of the measurement system. Finally, we challenge our RM-based solution on noise and analyze the corresponding false alarm rate metric. Our results demo nstrate that the proposed RM-based frequency recovery algorithm attains an appealing performance.
科研通智能强力驱动
Strongly Powered by AbleSci AI