Low signal-to-background ratio gm-apd lidar range parameter estimation method based on multi-scale tracking differentiator

Abstract

The application relates to a low signal-to-background ratio GM-APD laser radar distance parameter estimation method based on a multi-scale tracking differentiator, relates to the technical field of laser radar detection imaging, solves the problem that in the condition of a low signal-to-background ratio, the echo of a GM-APD laser radar is easily submerged by strong noise, leading to the degradation of distance parameter estimation performance and low target restoration degree, a double-scale tracking differentiator system is constructed, large-scale factors are used to capture the transient mutation characteristics of echo signals, and small-scale factors are used to estimate the overall evolution trend of the signals; the residual signals are obtained by taking the difference of the double-scale outputs, and are combined with the nonlinear mapping enhancement of the photon trigger probability characteristics, so that the noise is deeply suppressed and the target peak value is highlighted, and the peak threshold method is used to complete distance calculation. The method is free from the dependence on complex statistical models and spatial prior information, and uses a nonlinear dynamic tracking mechanism to realize the extraction of target information.

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