对NO3腔衰荡光谱(cavity ring-down spectroscopy, CRDS)探测系统中衰荡时间的准确提取方法进行了研究。 对衰荡时间有效快速的提取可以提高CRDS测量的精度和速度。 选取了五种常用的提取衰荡时间的拟合方法, 分别为快速傅里叶变换法、 离散傅里叶变换法、 线性回归总和法、 列文伯格-马夸尔特算法和最小二乘法。 采用以上五种算法对带有不同大小白噪声的模拟衰荡信号进行拟合, 并从受噪声影响情况、 拟合准确性和精度、 拟合速率, 三个方面对五种算法的拟合结果进行对比和分析, 结果表明列文伯格-马夸尔特算法和线性回归总和法准确度高、 抗噪能力强, 但列文伯格-马夸尔特算法拟合速率相对较慢。 选取衰荡时间的5～10倍为衰荡信号的最佳拟合波形长度, 此时五种算法拟合结果的标准偏差最小。 采用外部调制二极管激光器及高反腔搭建CRDS探测系统, 针对0.2%噪声的实验条件, 选取线性回归总和法和列文伯格-马夸尔特算法对实际测量的实验数据进行处理。 实验表明, 线性回归总和法拟合准确度和精度与列文伯格-马夸尔特算法相似, 但拟合速率比列文伯格-马夸尔特算法快约5倍。 实验结果与模拟分析相吻合, 表明线性回归总和法为适合我们实验条件的最佳拟合方法。

Research is conducted to accurate and efficient algorithms for extracting ring-down time (τ) in cavity ring-down spectroscopy (CRDS) which is used to measure NO3 radical in the atmosphere. Fast and accurate extraction of ring- down time guarantees more precise and higher speed of measurement. In this research, five kinds of commonly used algorithms are selected to extract ring-down time which respectively are fast Fourier transform (FFT) algorithm, discrete Fourier transform (DFT) algorithm, linear regression of the sum (LRS) algorithm, Levenberg-Marquardt (LM) algorithm and least squares (LS) algorithm. Simulated ring-down signals with various amplitude levels of white noises are fitted by using five kinds of the above-mentioned algorithms, and comparison and analysis is conducted to the fitting results of five kinds of algorithms from four respects: the vulnerability to noises, the accuracy and precision of the fitting, the speed of the fitting and preferable fitting ring-down signal waveform length. The research results show that Levenberg-Marquardt algorithm and linear regression of the sum algorithm are able to provide more precise results and prove to have higher noises immunity, and by comparison, the fitting speed of Levenberg-Marquardt algorithm turns out to be slower. In addition, by analysis of simulated ring-down signals, five to ten times of ring-down time is selected to be the best fitting waveform length because in this case, standard deviation of fitting results of five kinds of algorithms proves to be the minimum. External modulation diode laser and cavity which consists of two high reflectivity mirrors are used to construct a cavity ring-down spectroscopy detection system. According to our experimental conditions, in which the noise level is 0.2%, linear regression of the sum algorithm and Levenberg-Marquardt algorithm are selected to process experimental data. The experimental results show that the accuracy and precision of linear regression of the sum algorithm is considerably close to those of Levenberg-Marquardt algorithm, and on the other hand, the fitting speed of linear regression of the sum algorithm is faster than that of Levenberg-Marquardt algorithm about five times. The experimental results are consistent with the simulation analysis, and it indicates that linear regression of the sum algorithm is the desirable fitting method, as far as our experimental conditions are concerned.