Deep Learning Method on Target Echo Signal Recognition for Obscurant Penetrating Lidar Detection in Degraded Visual Environments

Liang, Xujia; Huang, Zhonghua; Lu, Liping; Tao, Zhigang; Yang, Bing; Li, Yinlin

doi:10.3390/s20123424

Cited by 8 publications

(2 citation statements)

References 31 publications

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“…According to the above analysis, the specific way is to compare the actual measured data of the detector prototype with the simulated data for the echo characteristics results in the same smoke visibility range. In order to obtain the measured data of the detector prototype, based on the FMCW laser detection process in Figure 1, by building a smoke test environment in the laboratory [37], the test parameters and process are shown in Figure 15a. The modules involved mainly include the following:…”

Section: Validity Experiments Of Laser Echo Characteristic Simulation...mentioning

confidence: 99%

Virtual Simulation of the Effect of FMCW Laser Fuse Detector’s Component Performance Variability on Target Echo Characteristics under Smoke Interference

et al. 2022

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The laser transmitter and photoelectric receiver are the core modules of the detector in a laser proximity fuse, whose performance variability can affect the accuracy of target detection and identification. In particular, there is no study on the effect of detector’s component performance variability on frequency-modulated continuous-wave (FMCW) laser fuse under smoke interference. Therefore, based on the principles of particle dynamic collision, ray tracing, and laser detection, this paper builds a virtual simulation model of FMCW laser transmission with the professional particle system of Unity3D, and studies the effect of performance variability of laser fuse detector components on the target characteristics under smoke interference. Simulation results show that the difference in the performance of the fuse detector components causes the amplitude variation and peak migration of the beat signal spectrum, and the change in the visibility of the smoke can also affect the results, which indicates that the factors affecting the signal-to-noise ratio (SNR) of the echo signal are related to the smoke interference and performance variability of the detector. The proposed simulation model is supported by experimental results, which reflect the reliability of the proposed findings. Therefore, this study can be used for the optimization of the parameters in the laser fuse antismoke interference to avoid false alarms.

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Section: Validity Experiments Of Laser Echo Characteristic Simulation...mentioning

confidence: 99%

Virtual Simulation of the Effect of FMCW Laser Fuse Detector’s Component Performance Variability on Target Echo Characteristics under Smoke Interference

et al. 2022

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“…In degraded visual environments such as fog, the detection of other traffic participants suffers. The paper [ 106 ] focuses on a LIDAR target echo signal recognition technology that is based on a multi-distance measurement and deep learning to detect obstacles. There are 2D spectrograms obtained by using the frequency–distance relation divided from 1D echo signals that the LIDAR sensor is providing.…”

Section: Sensors and Systems For Fog Detection And Visibility Enhancementmentioning

confidence: 99%

Visibility Enhancement and Fog Detection: Solutions Presented in Recent Scientific Papers with Potential for Application to Mobile Systems

Miclea

Ungureanu

Sandru

et al. 2021

Sensors

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In mobile systems, fog, rain, snow, haze, and sun glare are natural phenomena that can be very dangerous for drivers. In addition to the visibility problem, the driver must face also the choice of speed while driving. The main effects of fog are a decrease in contrast and a fade of color. Rain and snow cause also high perturbation for the driver while glare caused by the sun or by other traffic participants can be very dangerous even for a short period. In the field of autonomous vehicles, visibility is of the utmost importance. To solve this problem, different researchers have approached and offered varied solutions and methods. It is useful to focus on what has been presented in the scientific literature over the past ten years relative to these concerns. This synthesis and technological evolution in the field of sensors, in the field of communications, in data processing, can be the basis of new possibilities for approaching the problems. This paper summarizes the methods and systems found and considered relevant, which estimate or even improve visibility in adverse weather conditions. Searching in the scientific literature, in the last few years, for the preoccupations of the researchers for avoiding the problems of the mobile systems caused by the environmental factors, we found that the fog phenomenon is the most dangerous. Our focus is on the fog phenomenon, and here, we present published research about methods based on image processing, optical power measurement, systems of sensors, etc.

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Detection of Condensed Vehicle Gas Exhaust in LiDAR Point Clouds

Piroli

Dallabetta

Walessa

et al. 2022

2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC)

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Deep Learning Method on Target Echo Signal Recognition for Obscurant Penetrating Lidar Detection in Degraded Visual Environments

Cited by 8 publications

References 31 publications

Virtual Simulation of the Effect of FMCW Laser Fuse Detector’s Component Performance Variability on Target Echo Characteristics under Smoke Interference

Virtual Simulation of the Effect of FMCW Laser Fuse Detector’s Component Performance Variability on Target Echo Characteristics under Smoke Interference

Visibility Enhancement and Fog Detection: Solutions Presented in Recent Scientific Papers with Potential for Application to Mobile Systems

Detection of Condensed Vehicle Gas Exhaust in LiDAR Point Clouds

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