Poisson distribution model is the basis of data analysis for GM-APD lidar, but it is only applicable to the mirror reflected target under ideal conditions, and cannot accurately describe the photon triggering process of actual GM-APD lidar detection. For the actual target with rough surface, the negative binomial distribution with M as the parameter can describe the photon distribution model more accurately. In order to solve this problem, this paper compares and analyzes Poisson distribution triggering model and the negative binomial distribution triggering model that conforms to the triggering situation of the echo signal of the target with rough surface, considering the differences in the triggering probability under different noise and signal levels. The results show that the trigger probability curve corresponding to the trigger model based on negative binomial distribution is lower in peak value, wider in bottom value and fatter overall than that of the trigger model based on Poisson distribution, and the difference between the two is more prominent under the conditions of low noise level and high signal level. This study has guiding significance for the signal extraction research based on different surface echoes.
When using Geiger mode Avalanche Photo Diode (Gm-APD) array lidar for long-distance imaging, the few echo photons make it challenging to get the target position. To solve these problems, this paper proposes a spatial correlation extraction algorithm combined with morphological filtering (SCMF), which uses the spatial correlation of the target to superposition the weight of the pixel histogram, increasing the number of statistical frames, improving the signal-to-noise (SNR) of pixel statistical data and accurately extracting the distance value of the target pixel. Spatial correlation also improves the real-time imaging of the system. According to the time-domain spatial dispersion characteristics of residual noise pixels of small intensity threshold, a local spatial distance correlation logic method is proposed, which only preserves the pixel groups with similar spatial distances and removes the stray background noise pixels. Because the number of pixels in the target pixel group is more than the noise group, a spatial filter module is constructed using morphological filtering to remove the remaining blocky noise group and preserve the target pixel group. The proposed method can achieve long-distance imaging in 0.02s acquisition time through outdoor real imaging experiments. Under the echo condition of 0.0152 Signal to Background ratio (SBR), the SCMF method has 76% target restoration, and the reconstructed image SNR can improve 23 times compared with the peak-picking method, a great improvement has been made in the reconstruction of image denoising.
In recent years, the array Geiger-mode avalanche photodiode (Gm-APD) has become a research hotspot in the world due to its advantages of detection sensitivity, spatial resolution and range resolution. A set of 1064 nm laser active imaging experiment platform is built with the core device of 256×128 pixel domestic self-developed InGaAs material Gm-APD. The data of 500m and 350m targets in external field are obtained, and the three-dimensional distance image, intensity image and photon counting image are reconstructed by using single photon echo signal detection method. Through the experiment, the range resolution of the detector is 0.3m, and the contrast of the photon count intensity image are larger than the intensity image. It is proved that the self-develop array Gm-APD detector with 1064nm lase has good performance, and it can demonstrate the field laser active imaging function, which lays a good research foundation for future practical application.
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