光谱域编码的压缩光谱测量技术

光谱测量技术在生物医药、国防、安检、生产监控、地质勘测、物质分析、环境保护和减灾防灾等方面有着广泛的应用。但受制于现有探测器件和应用的技术条件，传统类型光谱仪在上述领域的应用灵活性和适用性的限制较多，光谱系统微型化和可集成化是确定发展的趋势之一。光谱成像系统有着向微型化、芯片化和智能化发展的迫切需求，且伴随相关计算光谱成像理论的成熟完善，计算型光谱仪有望在减少器件或系统重量与尺寸的同时，大幅提升光谱分辨能力。基于压缩感知理论的计算型光谱仪具有实时性好、适用范围广、结构调整灵活、成本低廉等诸多优势。文中参考压缩感知理论的基础框架，详细对比多种分光结构的设计方法，分析光谱域直接编码的压缩光谱测量技术，归纳总结具有压缩感知功能的智能芯片化光谱仪的发展趋势和技术问题。

Compressed spectral measurement technology based on coding of spectrum domain

Spectral detection technology has a wide range of applications in biomedicine, national defense, security check, production monitoring, geological survey, material analysis, environmental protection, disaster reduction and so on. However, due to the existing detectors and application technology conditions, the flexibility and applicability of traditional spectral instruments is limited in above territories. The miniaturization and integration of spectral systems is one of the inevitable development trends. With the critical demand of miniaturized, chip and intelligent spectral imaging and the maturation of the computational spectral imaging theory, computational spectrometers have attracted much attention because of the ability to improve spectral resolution while reducing the mass and volume of devices or systems. The computational spectrometers based on compressed sensing theory have the advantages of short calculation time, wide application range, flexible structure, low cost and so on. This review compares the design methods of various spectral structure based on the framework of compressed sensing theory, analyzes the compression spectral measurement technology which realizes the direct coding of spectrum domain and reveals the development trend and bottleneck of miniaturized, intelligent chip spectrometers based on compressed sensing algorithm.