基于光子辅助的压缩采样技术研究

发布时间：2018-05-12 16:20

本文选题：压缩采样 + 光子辅助　；参考：《清华大学》2014年博士论文

【摘要】：众所周知，与传统的采样技术相比，压缩采样技术在获取稀疏信号时具有采样率低、数据量小的优势，在雷达信号感知中得到广泛的应用。为了进一步有效提高处理频率和带宽，基于光子辅助的压缩采样技术应运而生。目前，光压缩采样技术仍然处于研究的初步阶段，在系统的物理实现和性能提升方面都有待深入的探索。本论文围绕其中四个关键问题展开研究。首先，针对多通道光压缩采样技术实现难的问题，论文提出基于光纤色散延时PRBS的多通道压缩采样系统方案，通过多路PRBS信号共享PRBS源和电光调制器，大幅度降低系统复杂度。同时，论文研究系统的信号模型，理论分析采用这种PRBS源时压缩频谱的误差来源。基于此，首次实现了带宽为5GHz的8通道光压缩采样实验系统。然后，为了进一步提高多通道光压缩采样的恢复概率，论文提出采用非线性延时的多通道PRBS信号来增强系统压缩传感矩阵的随机性，进而改善矩阵的等距性，并通过大量的随机样本仿真来验证系统传感矩阵这一特性。同时，实验实现从4路带宽为120MHz的压缩频谱中有效恢复出0.2-5GHz范围内多个不同频段信号。另外，为了提高任意的既定频带信号恢复性能，论文提出基于可调延时的多通道PRBS信号的多子带接收技术，仿真实现从带宽为信息率的压缩信号中恢复出任意、既定频带的双子带信号。接着，为了突破压缩采样带宽受限于PRBS码率的一半这一瓶颈，论文提出基于时域间插的多路光PRBS脉冲来提高系统带宽，同时仿真验证了超宽带压缩采样系统传感矩阵的等距性。实验利用码率为10.16Gbps的光PRBS脉冲实现了带宽为20GHz的压缩采样。最后，针对0/1强度的PRBS信号导致光压缩采样系统采样率高、数据量大的问题，本文提出基于相位调制与相干接收来产生RF与±1强度PRBS的混频信号的解决方案，分析混频信号误差的主要来源。基于此，实验实现了压缩比为25:1、带宽为5GHz的光压缩采样系统。
[Abstract]:It is well known that compared with the traditional sampling technique, the compressed sampling technique has the advantages of low sampling rate and small amount of data in the acquisition of sparse signals, so it is widely used in radar signal sensing. In order to further improve the processing frequency and bandwidth, photon-assisted compression sampling technology emerged as the times require. At present, the optical compression sampling technology is still in the preliminary stage of research, and the physical implementation and performance improvement of the system need further exploration. This paper focuses on four key issues. First of all, aiming at the difficulty of multi-channel optical compression sampling technology, this paper proposes a multi-channel compression sampling system based on fiber dispersion delay PRBS. The system complexity is greatly reduced by sharing PRBS source and electro-optic modulator with multi-channel PRBS signals. At the same time, the paper studies the signal model of the system, and theoretically analyzes the error source of the compressed spectrum when the PRBS source is used. Based on this, an 8 channel optical compression sampling system with bandwidth of 5GHz is implemented for the first time. Then, in order to further improve the recovery probability of multi-channel optical compression sampling, a nonlinear time-delay multi-channel PRBS signal is proposed to enhance the randomness of the system compression sensor matrix, and then to improve the isometric property of the matrix. A large number of random samples are simulated to verify the characteristics of the sensor matrix. At the same time, the experimental results show that multiple signals in the range of 0.2-5GHz can be effectively recovered from the compressed spectrum with 4 channels of bandwidth 120MHz. In addition, in order to improve the recovery performance of any given frequency band signal, this paper proposes a multi-channel PRBS signal multi-subband receiving technology based on adjustable delay. The simulation realizes the recovery of arbitrary signal from the compressed signal with bandwidth information rate. A Gemini signal in a given frequency band. Then, in order to break through the bottleneck that the compressed sampling bandwidth is limited to half of the PRBS bit rate, this paper proposes a multi-channel optical PRBS pulse based on interleaved time domain to improve the bandwidth of the system. At the same time, simulation verifies the equidistance of the sensor matrix of UWB compression sampling system. The compression sampling of 20GHz with bandwidth of 20GHz is realized by using optical PRBS pulse with bit rate of 10.16Gbps. Finally, aiming at the problem of high sampling rate and large amount of data in optical compression sampling system caused by 0 / 1 intensity PRBS signal, this paper proposes a solution to produce RF and 卤1 intensity PRBS mixed signal based on phase modulation and coherent reception. The main source of error of mixing signal is analyzed. Based on this, an optical compression sampling system with compression ratio of 25: 1 and bandwidth of 5GHz is implemented experimentally.
【学位授予单位】：清华大学
【学位级别】：博士
【学位授予年份】：2014
【分类号】：TN911.7

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