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Analyzing the performance of pseudo-random single photon counting ranging Lidar

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Abstract

The detection principle and performance of the pseudo-random single photon counting ranging (PSPCR) Lidar system are investigated. The detection probability and single photon detection efficiency (SPDE) of the macro code for the PSPCR Lidar system are derived based on statistical theory. The effects of the echo primary electrons number and the dead time on the detection probability and SPDE are analyzed. The detection probability increases with the increase of the primary electron number and tends toward saturation. The change of dead time length has little effect on the detection probability of the macro code, especially when the number of echo primary electrons is large. However, the length of dead time is inversely proportional to the number of detected codes. The longer the dead time, the fewer the number of detected codes, and the worse the ranging performance. The signal-to-noise ratio (SNR) of the PSPCR Lidar is analyzed based on the cross-correlation function. The Monte Carlo simulation results show that the PSPCR Lidar has a satisfactory SNR even in a high noise level. As the number of signal primary electrons increases, the SNR gradually increases and tends to be saturated. As the noise increases, the SNR gradually decreases, and the greater the noise, the more severe the SNR decreases. At the same time, based on the assumption that the power of the single code in Gaussian distribution and the time resolution of the photon counting module are less than the code width, the theoretical formula of the range error is deduced. The effects of the echo signal primary electron number and code width on the range error are analyzed. The results show that the fewer the primary electron numbers or the narrower the code width, the smaller the range error of the PSPCR Lidar system. The range error of the PSPCR Lidar system is verified by Monte Carlo simulation. The simulation results are in good agreement with the theoretical analysis.

© 2018 Optical Society of America

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