A Macro-Pulse Photon Counting Lidar for Long-Range High-Speed Moving Target Detection

Yu, Yang; Liu, Bo; Chen, Zhe; Li, Zhikang

doi:10.3390/s20082204

Cited by 10 publications

(6 citation statements)

References 19 publications

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“…Therefore, it is necessary to accumulate echo events. If the num-ber of accumulated events exceeds a certain threshold, the target is considered to be found [13,24,26]. An appropriate threshold and pulse accumulation number can effectively reduce the false-alarm probability and improve the detection performance.…”

Section: Single Photon Detection Model and Analysismentioning

confidence: 99%

“…Here, a frame is about 18 ms and the amount of data is relatively small, and assume that the data-processing time is negligible. The number of accumulated pulses can be up to 10 or more for Tout = 2 ms by the macro pulse method [13,33]. Meanwhile, the ability of the target tracking and detecting also can be improved.…”

Section: Analysis Of Tracking and Detection Capabilitymentioning

confidence: 99%

“…In this case, the SPD will allow the use of low-power laser sources to detect non-cooperative targets in conditions of a weak echo signal. Currently, most of the research mainly focuses on the rapid detection of weak signals, long-distance high-precision measurement, ranging performance, and imaging [13][14][15][16][17][18][19] based on single photon detection. However, there are few tracking researches based on single photon detection.…”

Section: Introductionmentioning

confidence: 99%

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Target Tracking and Ranging Based on Single Photon Detection

Liu

Wang

et al. 2021

Photonics

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In order to achieve non-cooperative target tracking and ranging in conditions of a weak echo signal, this paper presents a real-time acquisition, pointing, tracking (APT), and ranging (APTR) lidar system based on single photon detection. With this system, an active target APT mechanism based on a single photon detector is proposed. The target tracking and ranging strategy and the simulation of target APT are presented. Experiments in the laboratory show that the system has good performance to achieve the acquisition, pointing and ranging of a static target, and track a dynamic target (angular velocity around 3 mrad/s) under the condition of extremely weak echo signals (a dozen photons). Meanwhile, through further theoretical analysis, it can be proven that the mechanism has stronger tracking and detection ability in long distance. It can achieve the active tracking of the target with a lateral velocity of hundreds of meters per second at about one hundred kilometers distance. This means that it has the ability of fast long-distance non-cooperative target tracking and ranging, only by using a single-point single photon detector.

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Section: Single Photon Detection Model and Analysismentioning

confidence: 99%

Section: Analysis Of Tracking and Detection Capabilitymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Target Tracking and Ranging Based on Single Photon Detection

Liu

Wang

et al. 2021

Photonics

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“…Photon-counting LiDAR, equipped with a Geiger-mode avalanche photodiode (Gm-APD), has a high capability for photon-efficient sensitivity and picosecond-level time resolution and the potential for range detection and 3D imaging for remote targets [ 1 , 2 , 3 , 4 , 5 , 6 , 7 ]. Affected by the probabilistic response of the Gm-APD, the detection process of photon-counting LiDAR is statistical, which requires the accumulation of multiple pulses to locate the echo signal [ 8 , 9 , 10 ]. Nevertheless, in scenarios with strong background noise, the selection of the number of cumulative pulses is a common problem.…”

Section: Introductionmentioning

confidence: 99%

Prediction of the Number of Cumulative Pulses Based on the Photon Statistical Entropy Evaluation in Photon-Counting LiDAR

Huang

Zhang

Cen

et al. 2023

Entropy

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Photon-counting LiDAR encounters interference from background noise in remote target detection, and the statistical detection of the accumulation of multiple pulses is necessary to eliminate the uncertainty of responses from the Geiger-mode avalanche photodiode (Gm-APD). The cumulative number of statistical detections is difficult to select due to the lack of effective evaluation of the influence of the background noise. In this work, a statistical detection signal evaluation method based on photon statistical entropy (PSE) is proposed by developing the detection process of the Gm-APD as an information transmission model. A prediction model for estimating the number of cumulative pulses required for high-accuracy ranging with the background noise is then established. The simulation analysis shows that the proposed PSE is more sensitive to the noise compared with the signal-to-noise ratio evaluation, and a minimum PSE exists to ensure all the range detections with background noise are close to the true range with a low and stable range error. The experiments demonstrate that the prediction model provides a reliable estimation of the number of required cumulative pulses in various noise conditions. With the estimated number of cumulative pulses, when the signal photons are less than 0.1 per pulse, the range accuracy of 4.1 cm and 5.3 cm are obtained under the background noise of 7.6 MHz and 5.1 MHz, respectively.

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“…Similarly, with the rapid development of the times, more and more requirements for video processing applications have been put forward. Moving target detection work is involved in many engineering application projects, but the moving target has a certain degree of difficulty in moving target detection due to the strong time-varying speed and uncertain path [ 6 , 7 ]. Among them, the basketball special automatic test is an engineering application of sports target detection.…”

Section: Introductionmentioning

confidence: 99%

Concrete Application of Computer Virtual Image Technology in Modern Sports Training

Chi

Li²

2022

Computational Intelligence and Neuroscience

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The efficiency of basketball shooting training has always been an urgent problem to be solved in basketball sports. Applying computer virtual image technology to basketball sports training is the key to improve basketball shooting ability and improve the effect of basketball sports training. Therefore, based on the design of basketball shooting automatic recognition system based on the background difference method, this study puts forward the specific application of computer virtual image technology in modern sports training. By analyzing the techniques of image denoising, image detection, and image calibration, a goal detection algorithm for modern sports basketball shooting training is designed. Firstly, the camera is used for image capture, the RGB image is converted into gray image, and the median filter is used to suppress the noise in the image. Then, the background difference method is used to detect the moving region, and the background modeling is combined with the mean method. After obtaining the background reference model, the image is differentiated, the gray image after image difference is binarized, and then the binary image is postprocessed by morphological middle closure operation. Finally, the image calibration technology is used to extract the basketball feature information. Through the region segmentation algorithm, the basketball shooting part is segmented and judged, so as to realize the basketball shooting training goal detection. The experimental results show that the proposed method has a good effect on basketball shooting training goal detection and can effectively improve the detection accuracy and efficiency.

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A Macro-Pulse Photon Counting Lidar for Long-Range High-Speed Moving Target Detection

Cited by 10 publications

References 19 publications

Target Tracking and Ranging Based on Single Photon Detection

Target Tracking and Ranging Based on Single Photon Detection

Prediction of the Number of Cumulative Pulses Based on the Photon Statistical Entropy Evaluation in Photon-Counting LiDAR

Concrete Application of Computer Virtual Image Technology in Modern Sports Training

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