Abstract
In this paper, a true random coding photon counting LIDAR is described, in which a Gm-APD (Geiger mode avalanche photodiode) acts as the true random sequence signal generator. The true random coding method not only improves the anti-crosstalk capability of the system, but also greatly reduces the 1-bit missed detection caused by the limited Gm-APD count rate. The experiment verifies the feasibility of the true random sequence used in a photon counting LIDAR ranging system, and a simple and intuitive evaluation model of true random sequence autocorrelation is proposed. Finally, the influence of system parameters (mean echo photon number, mean pulse count density, sequence length, mean noise count) on detection probability is explored. In general, this paper proves that the true random code photon counting LIDAR is an effective target detection method, and provides a new idea for the research of an anti-crosstalk LIDAR system.
Highlights
The photon counting LIDAR has attracted the attention of researchers and is widely used in the fields of ranging and 3D imaging [1,2,3,4]
Differing from pseudo-random modulation, we propose a more innovative coding method that can be used for the photon counting LIDAR, called the true random coding method
The experiment shows that the mean echo photon number, the sequence length, the mean pulse count density and the mean noise count all affect the detection probability
Summary
The photon counting LIDAR (light detection and ranging) has attracted the attention of researchers and is widely used in the fields of ranging and 3D imaging [1,2,3,4]. The pseudo-random coding method was introduced into the photon counting laser altimeter system by Sun to realize the long-distance target ranging [12]. Using the pseudo-random coding photon counting LIDAR ranging technique, Zhang realized the detection of a non-cooperative target at 1.2 km [16]. Yang realized high spatial resolution detection using a high speed pseudo-random modulation photon counting fiber laser ranging system and verified that the ranging accuracy and SNR (Signal Noise Ratio) were improved with the increase in pseudo-random sequences. Zhang proved that the random coding method can effectively improve the detection speed compared with the pulse accumulation photon counting. The pseudo-random coding method improves the anti-noise capability of the photon counting LIDAR. We first elaborated the advantages of the true random coding method, established the ranging model, confirmed the feasibility of this method, and verified its detection performance by experiments
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