Mahjoubfar Ata, Chen Claire Lifan, Jalali Bahram
Department of Electrical Engineering, University of California, Los Angeles, California 90095, USA.
California NanoSystems Institute, Los Angeles, California 90095, USA.
Sci Rep. 2015 Nov 25;5:17148. doi: 10.1038/srep17148.
Time stretch dispersive Fourier transform enables real-time spectroscopy at the repetition rate of million scans per second. High-speed real-time instruments ranging from analog-to-digital converters to cameras and single-shot rare-phenomena capture equipment with record performance have been empowered by it. Its warped stretch variant, realized with nonlinear group delay dispersion, offers variable-rate spectral domain sampling, as well as the ability to engineer the time-bandwidth product of the signal's envelope to match that of the data acquisition systems. To be able to reconstruct the signal with low loss, the spectrotemporal distribution of the signal spectrum needs to be sparse. Here, for the first time, we show how to design the kernel of the transform and specifically, the nonlinear group delay profile dictated by the signal sparsity. Such a kernel leads to smart stretching with nonuniform spectral resolution, having direct utility in improvement of data acquisition rate, real-time data compression, and enhancement of ultrafast data capture accuracy. We also discuss the application of warped stretch transform in spectrotemporal analysis of continuous-time signals.
时间拉伸色散傅里叶变换能够以每秒百万次扫描的重复速率进行实时光谱分析。从模数转换器到相机以及具有创纪录性能的单次罕见现象捕获设备等高速实时仪器都因它而得到了提升。其通过非线性群时延色散实现的扭曲拉伸变体提供了可变速率的光谱域采样,以及设计信号包络的时间带宽积以匹配数据采集系统的时间带宽积的能力。为了能够低损耗地重建信号,信号频谱的光谱时间分布需要是稀疏的。在此,我们首次展示了如何设计变换的内核,特别是由信号稀疏性决定的非线性群时延分布。这样的内核会导致具有非均匀光谱分辨率的智能拉伸,在提高数据采集速率、实时数据压缩以及增强超快数据捕获精度方面具有直接用途。我们还讨论了扭曲拉伸变换在连续时间信号的光谱时间分析中的应用。