Compressive Sensing Reconstruction System and Method for Sparse Spectrum

Abstract

The invention discloses a compressed sensing reconstruction system for a sparse spectrum and a method thereof, which relate to a spectral measurement technology. In the system, an optical unit (10), a circuit conditioning unit (20), a data processing unit (30), a transmission unit (40) and an upper computer (50) are sequentially connected; and the data processing unit (30) and the optical unit (10) are connected. The method comprises steps of SAMP (Sparsity Adaptive Matching Pursuit compression sensing reconstruction algorithm selection and parameter optimization, partial Hadamard matrix modulation template generation and DMD (Digital Micro-mirror Device) control and data sparsity processing. The spectral generation cost can be reduced, and the data sampling time and the storage space are reduced; the system design complexity is simplified, and the system design cost is reduced; and a wireless transmission network is used to transmit sampling data to realize real-time processing, and the working efficiency is improved.

Description

technical field [0001] The invention relates to spectrum measurement technology, in particular to a sparse spectrum compressed sensing reconstruction system and method thereof. Background technique [0002] Conventional spectrometers based on the Nyquist sampling law can achieve high luminous flux and high resolution, but there is a problem of data redundancy during sampling, which requires a lot of sampling time and storage space; at the same time, in order to obtain enough information, the required sampling speed and processing speed are getting higher and higher. Compressed sensing can better compensate for the defects of the Nyquist sampling law, inject new vitality into the development of existing spectrometers, and has received extensive attention in different fields. In 2004, Donoho and Candes of Stanford University in the United States proposed the compressed sensing theory for the first time, proving that a finite-dimensional signal with sparsity or compressibility...

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to provide a system and method for compressive sensing reconstruction of sparse spectra to solve a series of problems such as redundant sampling data, long sampling period and waste of storage resources in the restoration process of sparse spectra in traditional spectrometers, so as to realize Reconstructing Spectra Using Compressed Sensing at the Cost of Smaller Measurements

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