Multi-beam single-photon-counting three-dimensional imaging lidar

Li, Zhaohui; Wu, E; Pang, Chengkai; Du, Bingcheng; Tao, Yuliang; Peng, Huan; Zeng, Heping; Wu, Guang

doi:10.1364/oe.25.010189

Cited by 67 publications

(18 citation statements)

References 23 publications

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“…Laser detection and ranging (lidar) has been widely used in topographic mapping, ocean detection, unmanned driving and other fields due to its advantages of high transmission efficiency, small size, and high resolution [1][2][3]. Recently, ranging and imaging lidar of tens of kilometers has been realized based on a single-photon detector, which is one of the most sensitive optical detection techniques [4][5][6][7][8][9]. Under strong background light, a single-photon detector will output a large number of noise counts or even saturation.…”

Section: Introductionmentioning

confidence: 99%

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Portable Pulsed Coherent Lidar for Noncooperation Targets at the Few-Photon Level

Pang

Zhang

et al. 2021

Sensors

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The decoherence in coherent lidar becomes serious with the increase in distance. A small laser spot can suppress the decoherence of the echo light from noncooperation targets. However, it is very difficult to keep a small light spot over a long distance. In this paper, a pulsed coherent lidar with high sensitivity at the few-photon level was demonstrated. A phase plate was used to modulate the wavefront of the laser to achieve 100 m focusing which reduced the decoherence effect. Based on coherent detection and time-of-flight (TOF) measurements, long-distance laser ranging and imaging on all days was realized. A signal classification and superposition method was used to extract the echo signal submerged in noise. The system was experimentally demonstrated by ranging different noncooperation targets within 105.0 m. The measurement rate was 10 k/s, and the measurement uncertainty was 1.48 cm. In addition, laser imaging was realized at ~50.0 m. The system was simple and portable as well as eye safe, and it may offer new application possibilities in automated vehicle lidar.

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Section: Introductionmentioning

confidence: 99%

“…A small light spot can suppress the decoherence of the echo light from noncooperation targets. However, the laser spot of the lidar is usually larger than 20 mm in diameter while the distance is longer than 100.0 m [6,9]. It is very difficult to keep a small light spot over a long distance.…”

Section: Introductionmentioning

confidence: 99%

Portable Pulsed Coherent Lidar for Noncooperation Targets at the Few-Photon Level

Pang

Zhang

et al. 2021

Sensors

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“…TCSPC was mainly used in the detection of fluorescence lifetime in the early stage [4][5][6][7][8][9][10][11][12]. After that, TCSPC began to be used in the field of laser ranging [13][14][15][16][17][18] and gradually developed to the direction of laser long-distance 3D imaging based on time-of-flight (TOF) algorithm [19][20][21][22][23][24][25][26]. Recently, Li et al achieved the imaging of targets 45 kilometers away [27].…”

Section: Introductionmentioning

confidence: 99%

Three-Dimensional Imaging via Time-Correlated Single-Photon Counting

Zheng

Gao

et al. 2020

Applied Sciences

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Three-dimensional (3D) imaging under the condition of weak light and low signal-to-noise ratio is a challenging task. In this paper, a 3D imaging scheme based on time-correlated single-photon counting technology is proposed and demonstrated. The 3D imaging scheme, which is composed of a pulsed laser, a scanning mirror, single-photon detectors, and a time-correlated single-photon counting module, employs time-correlated single-photon counting technology for 3D LiDAR (Light Detection and Ranging). Aided by the range-gated technology, experiments show that the proposed scheme can image the object when the signal-to-noise ratio is decreased to −13 dB and improve the structural similarity index of imaging results by 10 times. Then we prove the proposed scheme can image the object in three dimensions with a lateral imaging resolution of 512 × 512 and an axial resolution of 4.2 mm in 6.7 s. At last, a high-resolution 3D reconstruction of an object is also achieved by using the photometric stereo algorithm.

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“…The ultimate goal of imaging is to fully understand and classify detected objects based on information acquired from a target. With the continuous development of remote sensing technologies, imaging methods have become diversified [8,9].…”

Section: Introductionmentioning

confidence: 99%

True-Color Three-Dimensional Imaging and Target Classification BASED on Hyperspectral LiDAR

et al. 2019

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True-color three-dimensional (3D) imaging exploits spatial and spectral information and can enable accurate feature extraction and object classification. The existing methods, however, are limited by data collection mechanisms when realizing true-color 3D imaging. We overcome this problem and present a novel true-color 3D imaging method based on a 32-channel hyperspectral LiDAR (HSL) covering a 431–751 nm spectral range. We conducted two experiments, one with nine-color card papers and the other with seven different colored objects. We used the former to investigate the effect of true-color 3D imaging and determine the optimal spectral bands for compositing true-color, and the latter to explore the classification potential based on the true-color feature using polynomial support vector machine (SVM) and Gaussian naive Bayes (NB) classifiers. Since using all bands of HSL will cause color distortions, the optimal spectral band combination for better compositing the true-color were selected by principal component analysis (PCA) and spectral correlation measure (SCM); PCA emphasizes the amount of information in band combinations, while SCM focuses on correlation between bands. The results show that the true-color 3D imaging can be realized based on HSL measurements, and three spectral bands of 466, 546, and 626 nm were determined. Comparing reflectance of the three selected bands, the overall classification accuracy of seven different colored objects was improved by 14.6% and 8.25% based on SVM and NB, respectively, classifiers after converting spectral intensities into true-color information. Overall, this study demonstrated the potential of HSL system in retrieving true-color and facilitating target recognition, and can serve as a guide in developing future three-channel or multi-channel true-color LiDAR.

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Multi-beam single-photon-counting three-dimensional imaging lidar

Cited by 67 publications

References 23 publications

Portable Pulsed Coherent Lidar for Noncooperation Targets at the Few-Photon Level

Portable Pulsed Coherent Lidar for Noncooperation Targets at the Few-Photon Level

Three-Dimensional Imaging via Time-Correlated Single-Photon Counting

True-Color Three-Dimensional Imaging and Target Classification BASED on Hyperspectral LiDAR

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