To further effectively suppress the noise of the detection system and improve the detection accuracy, an improved minimum mean squared deviation adaptive algorithm is studied for noise reduction in the methane concentra- tion detection system of tunable diode laser absorption spectroscopy. Through matlab simulation experiments based on TDLAS technology, the methane detection system is built, and the methane absorption peak position at 1 653. 72 nm is selected to analyze the relationship between the filtering order, step factor and sampling period on noise in the LMS adaptive algorithm, and improve the selection of parameters to optimize the noise reduction process with the best filte- ring effect. It is shown that the optimal filtering effect can be achieved by converging to the optimal filtering order and step factor at the high frequency sampling time. The results show that the signal-to-noise ratio is effectively improved by 94% and the goodness-of-fit R2 reaches 0. 997, which proves that the improved LMS adaptive filtering algorithm can effectively suppress the effect of noise on the second harmonic signal.