中文摘要：

针对光纤布拉格光栅（FBG）传感信号难以去除噪声干扰及信号丢失问题,采用压缩感知（CS）对传感信号进行处理。CS重构算法多是以稀疏度已知为先验条件,提出稀疏度确定方法,结合二次正交匹配追踪（TOMP）算法和广义正交匹配追踪（GOMP）算法提出广义二次正交匹配追踪（GtOMP）算法,确定每次迭代选择原子个数及迭代次数。首先计算相关系数,归一化后按降序排列,并结合饱和值的方法确定稀疏度,利用平稳度找出每次迭代所选择的原子个数,最后利用本文方法对FBG信号进行重构。实验仿真表明,与同类的TOMP算法相比,本文算法不仅运行时间大大减少,而且降低了6~20%的重构误差;与其他不同类算法相比,本文算法重构信号的信噪比（SNR）提高27dB以上。

英文摘要：

Abstract：Aiming at that it is difficult to solve the 1/f noise removing and the loss of signal for fiber Bragg gratting （FBG） sensing signal,the compressed sensing （CS） is used to process the sensing signal in this paper. But CS takes the sparsity as priori condition. The sparsity is determined with innovation method proposed in this paper, a new algorithm which is called group twice orthogonal matching pursuit （GtOMP） based on twice orthogonal matching pursuit （TOMP） and group orthogonal matching pursuit （GOMP） is proposed,and the number of atoms in each iteration as well as the number of iteration is ob- tained. First of all, the calculated and normalized correlation coefficients in descending order used with the method of saturation value to determine the sparsity. And the number of atoms each iteration is con- firmed by using smoothness. In the end, the proposed method is applied to reconstruct the FBG signal. Simulatin results show that, compared with the similar TOMP algorithm, the algorithm in this paper not only reduces the running time, but also decreases the reconstruction error of 6;20; ,and compared with other algorithms, signal noise ratio （SNR） of the signal after processing by the proposed method can be improved by more than 27 dB.