Afterpulse correction algorithm for differential absorption lidar based on grid sampling and optimization

Differential absorption lidar (DIAL) is widely used to monitor spatial and temporal variations in the distribution of atmospheric gases, such as CO₂ and O₃. Single-photon detectors are critical components of DIAL systems, and their afterpulse effect can distort echo signals, significantly compromising the accuracy of gas concentration inversion. This study introduces an intelligent optimized afterpulse correction algorithm that utilizes differences in signal response between two detectors. The algorithm evaluates the afterpulse characteristics of the detectors and applies real-time corrections during signal processing. This effectively mitigates the interference caused by strong afterpulse effects on signal integrity. Comparative experiments with real lidar signals demonstrate that this algorithm substantially enhances the detection performance of DIAL systems. Notably, the proposed method enables online evaluation and calibration of the afterpulse effect using lidar signals. Unlike traditional calibration approaches that rely on pre-installation detector testing, this technique provides a more thorough evaluation and effectively addresses the worsening of afterpulse effects due to aging lidar system components. The results show that this method increases the maximum nighttime detection range of the differential absorption lidar from 1500 m to 2000 m.