针对现有光栅光谱解调方式所需数据量较大不利于数据传输及处理的现状，应用压缩感知算法通过少量光谱数据采集实现高精度光栅光谱的重构。选取可调谐法布里珀罗(F-P)滤波器解调方式（TFPDA）作为参照并以布拉格光栅(FBG)及线性啁啾布拉格光栅(LCFBG)作为研究对象，构建实验平台验证压缩感知算法光谱重构的可行性。通过TFPDA采集及压缩感知算法重构不同温度下的光纤光栅光谱并通过高斯非线性算法拟合得FBG中心波长。实验数据表明通过压缩感知采集得FBG温度敏感系数为20.3 pm/℃，与TFPDA的相对误差为0.5%。对比此两种方法所得LCFBG光谱，其3 dB带宽内的最大相对误差为1.03%，中心波长处为0.69%。上述实验结果证实压缩感知算法在光栅光谱采集重构方面具有一定的应用价值。

Based on the status that the existing grating spectrum demodulation methods require large amount of data which limited the data transformation and processing, compressed sensing is introduced to reconstruct high-precision grating spectrum through acquiring a few spectrum data. Fiber Bragg grating (FBG) and linearly chirped fiber Bragg grating (LCFBG) are selected as the research objects. Grating spectrum FBG calibration experiment platform is built with tunable Fabry-Perot (F-P) filter demodulation algorithm (TFPDA) as the reference to validate the reconstructing practicability of compressed sensing. Gaussian nonlinear curve fitting is utilized to extract the center wavelengths reconstructed by TFPDA and compressed sensing under different temperatures. TBG temperature sensitivity coefficient obtained by compressed sensing is 20.3 pm/℃. Compared with the coefficient obtained by TFPDA, the relative error is 0.5%. Comparative analysis of LCFBG spectra collected by these two methods, the maximum error in 3 dB bandwidth is 1.03% and center wavelength is 0.69%. All these experimental results confirm that compressed sensing has certain application value in grating spectrum acquisition and reconstruction.