Photon counting method for atmospheric LiDAR echo signals based on waveform decomposition

To address the issue of photon counting rate saturation distortion caused by the photon pulse stacking effect in the photomultiplier tube (PMT) output of atmospheric LiDAR systems, a photon counting method for LiDAR echo signals based on waveform decomposition is proposed. This method simulates the single-photon pulse response waveform of the PMT and uses it as the basis function for waveform decomposition. The Levenberg–Marquardt fitting optimization algorithm is then applied to separate the photon components from the full waveform signal. Additionally, an algorithm is proposed to locate missing photons based on a local evaluation function and insert photons into these positions, solving the problem of initial parameter determination for the stacked components, which enables the counting of photons whose peaks are obscured due to the stacking effect. The experimental results indicate that, for echo signals sampled at 1 GHz, this method increases the upper limit of the photon counting rate from 200 to 500 MHz compared to traditional peak detection counting methods, which expands the effective measurement range of photon counting methods.