提出了一种将遗传算法(GA)和量子粒子群(QPSO)算法相结合的新优化算法，该算法通过运用GA 中的交叉和变异算子操作来优化QPSO 算法，提高QPSO 的全局搜索能力，克服其易陷入局部极值的缺点。将其应用到Pseudo-Voigt型布里渊散射谱特征提取，对不同权重比、不同线宽和不同信噪比下的布里渊散射谱进行了参数估计和分析，通过采集不同温度时的布里渊散射谱实验数据，利用GA-QPSO 算法对实验数据进行处理。实验结果表明，利用GA-QPSO 算法可以提高布里渊散射谱的频移提取精度，当温度为25 ℃时，频移拟合误差最大为2.18 MHz，且随着温度的升高，平均拟合误差逐渐减小，在80 ℃时的频移拟合误差最大为0.065 MHz。因此，将该算法用于布里渊散射温度和应变传感系统，在提高空间分辨率、检测精度等方面具有很好的应用前景。

A new optimization algorithm is presented, which is based on the genetic algorithm (GA) and quantumbehaved particle swarm optimization (QPSO) algorithm. The algorithm uses the crossover and mutation operators of GA to optimize the QPSO algorithm, improves its global search ability and overcomes the disadvantage that QPSO algorithm easily falls into local extremum. It is used to extract the character of the Pseudo-Voigt-shaped Brillouin scattering spectrum. The parameters estimation and simulation analysis of Brillouin scattering spectrum are analyzed under different weight ratios, line widths and signal-to-noise ratios. The experimental data of Brillouin scattering spectrum are collected in different temperatures and processed by GA-QPSO algorithm.The experimental results show that the GA-QPSO algorithm can improve the frequency shift extraction accuracy of Brillouin scattering spectrum. The maximum error of frequency shift fitting is 2.18 MHz under 25 ℃ and the average fitting error decreases with the increase of temperature, gradually.The frequency shift fitting maximum error is 0.065 MHz under 80 ℃. Therefore, the new algorithm can be used for measuring the temperature and strain in Brillouin scattering sensing system. It has a very good application prospect in improving spatial resolution and detection precision.