Gm-APD LiDAR Reconstruction Algorithm with Improved Matched Filtering Based on Negative Binomial Distribution

This article addresses the challenges faced by Gm-APD detectors in lidar systems when detecting weak signals. We use a triggering model based on the negative binomial distribution, which replaces the traditional Poisson distribution model, allowing for a more accurate description of the echo characteristics from rough surface targets. Building on this foundation, we have improved the conventional matched filtering algorithm by integrating the laser pulse waveform with the actual triggering response of the detector, thereby enhancing the detection rate. Experimental results demonstrate that the improved algorithm significantly increases the detection probability under low signal-to-noise ratios and with a limited number of frames, confirming the effectiveness of the new triggering model and the enhanced algorithm.