基于双高斯方差优化的Gm-APD 三维距离像预处理方法研究

The target detection probability and target reduction degree of the three -dimensional reconstruction algorithm of Geiger mode Avalanche Photo Diode (Gm -APD) laser imaging radar are greatly affected by the preprocessing. Improper preprocessing will cause the target to be missing and reduce the signal-to-noise ratio. Preprocessing usually uses Gaussian function or double Gaussian function for convolution, and improper variance in the filter function will also lead to lower target restoration. To improve this problem, the influence of the double Gaussian function preprocessing variance combination on the detection probability was analyzed. Then, Monte Carlo simulation was used to analyze the best variance combination varies in different background noise under fixed laser energy and frame number. The best variance model was obtained by fitting. Finally, reality experiment was used for verification, and the best variance combination obtained by the variance model can reach more than 90% of the best target reduction degree of actual reality. This model has theoretical guidance for actual signal processing.