Microwave spectral analysis based on photonic compressive sampling with random demodulation.
Microwave spectral analysis based on photonic compressive sampling with random demodulation.
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DOI：
10.1364/ol.37.004636
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发表时间：
2012-11
期刊：
影响因子：
3.6
通讯作者：
H. Chi;Yuan Mei;Ying Chen;Donghui Wang;Shilie Zheng;Xiaofeng Jin;Xianmin Zhang
中科院分区：
文献类型：
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作者：
H. Chi;Yuan Mei;Ying Chen;Donghui Wang;Shilie Zheng;Xiaofeng Jin;Xianmin Zhang
在这封信中，我们提出了一种基于光学采样和随机解调的微波频谱分析的光子压缩采样方案。提出了一种新的（据我们所知）在光域中实现伪随机二进制序列与感兴趣的输入微波信号相乘的方法，该方法大大简化了压缩采样的实现。利用随机解调和稀疏重构算法，在采样率远低于奈奎斯特采样率的情况下，电数字化仪可以成功地捕获频谱稀疏的信号。成功地证明了具有多个频率分量的信号的识别。
In this Letter, we present a photonic compressive sampling scheme based on optical sampling and random demodulation for microwave spectral analysis. A novel (to our knowledge) approach to realizing the multiplication of a pseudorandom binary sequence and the input microwave signal of interest in the optical domain is proposed, which largely simplifies the implementation of the compressive sampling. A spectrally sparse signal can be successfully captured by an electrical digitizer with a sampling rate much lower than the Nyquist rate with the help of random demodulation and the sparse reconstruction algorithm. Identification of the signals with multiple frequency components is successfully demonstrated.