GpDiff-QRNG: An Improved Quantum Random Number Generator for LiDAR Interference Suppression

The challenges of optical interference and attacks are crucial in light detection and ranging (LiDAR) sensors. Random modulation of transmitted laser can effectively suppress interference and counter attacks. The robustness of LiDAR sensors to interference and attacks completely depends on the use of high-quality random numbers. Quantum random number generation (QRNG) provides an excellent solution for true random number generation due to the inherent probability properties of quantum processes. Using the built-in single-photon avalanche diode (SPAD) array of LiDAR to obtain random numbers has become an efficient QRNG solution. However, the current QRNG method only utilizes the temporal information of single-photon detection, resulting in low QRNG rates, especially under low light flux conditions. To this end, we propose a method to improve the QRNG rate, which generates quantum random numbers through pixel grouping in the spatial dimension and arrival time difference in the temporal dimension (GpDiff-QRNG). Experimental results indicate that the GpDiff-QRNG method significantly enhances the QRNG rate. In scenarios with a photon event probability of 1%, the QRNG rate of the GpDiff-QRNG method is 37 times higher than that of the traditional QRNG by difference of arrival time (Diff-QRNG) method. Furthermore, the random sequences generated by the GpDiff-QRNG method exhibit no periodicity and belong to pure random sequences of white noise. Our method greatly expands the application of QRNG for LiDAR anti-interference and anti-attack.