A new method for estimating the noise scale factor (NSF) and random errors in lidar observations

Abstract

The noise scale factor (NSF) is useful in calculating the random errors of lidar signals. A new method is proposed for estimating the NSF of lidar systems. Instead of measuring the solar background in the traditional method that demands special experiments or additional devices, the new method utilizes the molecular backscattered signal fragments of routinely observed lidar profiles to extract the light intensities and shot noises. Based on a 355 nm lidar system, experiments with the two methods have been carried out. The NSF calculated with the new method is 0.6473, very close to the value resulted from the traditional method, which is 0.6496. The experiments indicate that the new method is feasible and accurate. An example of calculating the random errors and signal to noise ratios (SNR) of lidar signals by using NSF is presented. Compared with the results calculated from multiple lidar profiles, the method using NSF eliminates the influence of aerosols and clouds.

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Acknowledgements

This work was supported by the National Key Research and Development Program of China (2017FYC0209803, 2017YFC0210106, and 2018YFC0213503) and the National Natural Science Foundation of China (41621005).

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Correspondence to Tijian Wang.

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Zhao, M., Wang, T., Wu, H. et al. A new method for estimating the noise scale factor (NSF) and random errors in lidar observations. Appl. Phys. B 127, 21 (2021). https://doi.org/10.1007/s00340-021-07572-2

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