FTIR Noise Calibration in Quantitative Estimate of VOCs Concentration
WANG Xin1, LI Yan1, WEI Hao-yun1, REN Li-bing1, QI Yang2
1. State Key Laboratory of Precision Measurement Technology and Instruments, Department of Precision Instrument, Tsinghua University, Beijing 100084, China 2. Institute for Advanced Study, Tsinghua University, Beijing 100084, China
Abstract：The Classical Least Square regression (CLS) is one of the most popular regression methods in FTIR quantitative estimation. However, CLS is the best unbiased estimator only under the assumption that error (noise) in the spectrum has equal variance, which usually is not the case in FTIR. This paper proposed a noise calibration method for FTIR spectrum analysis. Based on measured variance of noise in the FTIR spectrum by computer, the Weighted Least Square regression (WLS) method is used in quantitative estimation. The experiment results showed that the WLS performs much better than CLS in quantitative estimation of VOCs pollution.
Key words：Fourier transform infrared spectroscopy;Classical least square regression;Weighted least square regression;Noise to signal ratio
