AI Article Synopsis

  • Single-photon LiDAR is commonly used for creating 3D scene reconstructions but faces noise issues that affect depth and reflectivity maps.
  • Traditional threshold detection techniques help reduce noise by filtering low photon counts but lose important information and don't perform well in challenging, noisy environments.
  • The proposed detection method merges noise suppression from threshold detection and signal amplification from photon-number-resolving detectors, leading to improved LiDAR performance demonstrated through simulations and experiments, resulting in better quality depth and reflectivity maps.

Article Abstract

Single-photon light detection and ranging (LiDAR) is widely used to reconstruct 3D scenes. Nevertheless, depth and reflectivity maps obtained by single-photon detection usually suffer from noise problems. Threshold LiDAR techniques using photon-number-resolving detectors were proposed to suppress noise by filtering low photon numbers, but these techniques renounce multiple levels of information and could not be compatible when it comes to high-noise low-signal regime. In this manuscript, we propose a detection scheme which combines the noise suppression of threshold detection with the signal amplification of photon-number-resolving detectors to further enhance LiDAR performance. The enhancement attained is compared to single-photon and threshold detection schemes under a wide range of signal and noise conditions, in terms of signal-to-noise-ratio (SNR), detection rate and false alarm rate, which are key metrics for LiDAR. Extensive simulations and real-world experiments show that the proposed scheme can reconstruct better depth and reflectivity maps. These results enable the development of high-efficient and low-noise LiDAR systems.

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Source
http://dx.doi.org/10.1364/OE.509252DOI Listing

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