Extinction Coefficient Inversion Algorithm with New Boundary Value Estimation for Horizontal Scanning Lidar

Abstract

Lidar has been used for many years to study the optical properties of aerosols, but estimating the boundary values requires solving the lidar elastic scattering equation, which remains a challenge. The boundary values are often determined by fitting to uniform regions of the atmosphere. This method typically excludes low signal-to-noise ratio (SNR) signals because it classifies them as non-uniform, reducing the effective detection range of the lidar. On the other hand, directly fitting low SNR signals to estimate the boundary values can introduce significant errors. The method is based on maximizing the lidar detection distance and determines the boundary value using a new estimation algorithm with the averaging of multiple fitted results in the low SNR region to reduce the impact of noise. Simulations demonstrate that the new method reduces the relative error in the boundary value estimation by approximately 5% and improves the accuracy of the extinction coefficient profile inversion compared with the method of directly fitting all-sample signals. Field comparison experiments with forward-scattering sensors further verify that the algorithm improves the retrieval accuracy by 17.3% under extremely low signal-to-noise ratio (SNR) conditions, while performing comparably to the traditional method in high SNR homogeneous atmospheres. Additionally, based on the scanned lidar signals, the algorithm can provide detailed information on the spatial distribution of sea fog and offer valuable insights for an in-depth understanding of the physical evolution of sea fog.

Keywords

• aerosol extinction coefficient inversion
• boundary value estimation
• Fernald method
• lidar
• remote sensing