Realization of quantum lidar imaging system

Bi, Sheng; Zhu, Hailong; Du, Jingshi; Zhou, Zongtan; Chen, Hao; Shen, Min; Zhang, Shoukai

doi:10.1117/12.2568284

Cited by 1 publication

(1 citation statement)

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“…After more than 20 years of combining theory and experiment, our team has completed high-sensitivity target detection, high-resolution imaging technology solutions and imaging principle experiments, elaborated the application of monochromatic quantum spectroscopy in imaging and detection [4] [5] , and also developed a principle prototype of quantum lidar for high-resolution imaging [6][7] [8] , and simultaneously also studied quantum enhancement, denoising, and segmentation algorithms [9]- [12] , and the earliest quantum lidar prototypes were reached through a combination of software and hardware [13] .The prototype currently enables quantum remote sensing of primary targets at a detection distance of one kilometre and can be used in a number of applications such as unmanned vehicles, smart cities, maritime detection, airport runways, helicopter obstacle avoidance and other areas,with significantly improved safety.…”

Section: Introductionmentioning

confidence: 99%

Technology research of 1km quantum lidar system

Bi,

Sheng,

Zhou

et al. 2023

Infrared Remote Sensing and Instrumentation XXXI

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Lidar (laser radar) offers advantages over conventional radar in terms of higher resolution, greater Anti-interference capability and Ultra-low altitude detection performance. However, Lidar has now reached a bottleneck in terms of detection range and is no longer able to correctly identify targets beyond 500 meters, thus failing to meet the requirements for detection, measurement and imaging.To break this bottleneck, we have developed a Quantum Lidar with a detection range of up to one kilometre, which is based on a quantum vacuum squeezed laser and can compress the photon fluctuation by 5.6dB in the vacuum state through quasi-phase matching in non-linear crystals, reducing the quantum noise of laser which accounts for 73% of the lidar, thus reducing the overall noise of the quantum lidar by 3.27dB and improves the phase stability of the laser (from 10 minutes to more than 120 minutes) to achieve higher accuracy measurements, with a Signal-Noise Ratio (SNR) twice that of conventional lidar, and therefore a sensitivity twice as high.The basic technical implementation is to use a 20W power 1064nm wavelength continuous wave laser (CW, M ² less than or equal to 1.05) to irradiate a target located one kilometre away. By detecting a very weak reflected laser (power=10μW ± 5μW) which is exponentially attenuated by distance, We use noiseless amplification by a quantum vacuum-squeezed laser with the same power magnitude to obtain a higher power (7dB amplification) and higher signalnoise ratio ( 4.77dB SNR improvement). A reflective lens set (250mm aperture) of our design is used to receive the laser diffusion due to the 4mrad transmission angle of one kilometre.In the squeezed laser system, the resonant cavity locking efficiency is improved to 99.7%, and the re-locking time is less than 0.3s, it is directly switchable with the balance homodyne detection system. The mode cleaner improves the transverse mode quality(the mode bandwidth is reduced by 67%) while filtering high-frequency noise.The quantum lidar imaging system has been developed, and the experimental results show that the resolution of the laboratory-simulated long-range decay experiment is 3 times higher than that of traditional lidar is a promising development. This means that the system can detect and image smaller objects and features with greater accuracy and precision.The use of a self-developed quantum enhancement algorithm to obtain a 5 times higher contrast lidar image is also a significant improvement, and the use of a quantum denoising algorithm to reduce graphic distortion and image scatter caused by atmospheric pollution and environmental interference is a critical development. These issues can significantly degrade the quality of lidar images, so being able to mitigate their effects is a significant step forward.Through a self-developed LiDAR 3D reconstruction algorithm, the reconstruction efficiency is increased by 3 times and the resolution is increased by 2.5 times ， which means that the reconstructed 3D model is faster, more detailed and accur...

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