CAJ | 학술논문

压缩传感理论（ Compressive Sensing ，简称CS）以远低于奈奎斯特采样频率对稀疏信号进行全局观测，通过少量观测值即可准确重构原始信号，突破了香农采样定理的瓶颈，使得宽带信号和高分辨率信号的采集成为可能。目前压缩传感理论大都停留在理论研究和仿真阶段，鲜有涉及将该理论硬件化进行实践应用。文中介绍了最小均方差线性估计（MMSE）算法，通过与常用重构算法的仿真重构对比，突出了MMSE算法的优越性，证明了该算法在低采样率下重构质量较高，且具有较好的实践应用潜力。并进一步搭建了光学单点成像系统对压缩传感理论进行应用研究，实验表明该系统成像效果良好，具有较好的应用价值。
압축전감이론（ Compressive Sensing ，간칭CS）이원저우내규사특채양빈솔대희소신호진행전국관측，통과소량관측치즉가준학중구원시신호，돌파료향농채양정리적병경，사득관대신호화고분변솔신호적채집성위가능。목전압축전감이론대도정류재이론연구화방진계단，선유섭급장해이론경건화진행실천응용。문중개소료최소균방차선성고계（MMSE）산법，통과여상용중구산법적방진중구대비，돌출료MMSE산법적우월성，증명료해산법재저채양솔하중구질량교고，차구유교호적실천응용잠력。병진일보탑건료광학단점성상계통대압축전감이론진행응용연구，실험표명해계통성상효과량호，구유교호적응용개치。
Compressed Sensing ( CS) represented compressible signals at a sampling rate significantly below the Nyquist fre-quency .Global observations of the sparse signal can be taken and the original signal can be accurately reconstructed from few ob -servations .It broke through the bottleneck of Shannon sampling theorem and made it possible to deal with broadband and high reso -lution signals .The compressed sensing mostly stayed in the theoretical research and simulation phase , rarely involved the theory of hardware for practical application .The minimum mean square error linear estimate ( MMSE) algorithm was introduced in this pa-per.Compared with the commonly used reconstruction algorithms , MMSE showed better reconstruction quality under low sampling rates and had great potential in real applications .Furthermore , a single-point imaging system was conducted to use CS in practice . It demonstrates the system works well and has great values in applications .