Noise modeling, evaluation and reduction for the atmospheric lidar technique employing an image sensor

Mei, Liang; Zhang, Lishan; Kong, Zheng; Li, Hui

doi:10.1016/j.optcom.2018.05.072

Cited by 33 publications

(16 citation statements)

References 29 publications

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“…The exposure time of the CMOS camera is automatically changed during 24-h continuous measurements to optimize the SNR [ 32 ], e.g., 20 ms under full sunshine and 500 ms during nighttime. The averaging number for a single lidar curve is also changed in order to keep identical total measurement time for each lidar curve, e.g., 1000 times @20 ms exposure time and 40 times @500 ms exposure time.…”

Section: Methodsmentioning

confidence: 99%

Atmospheric Pollution Monitoring in Urban Area by Employing a 450-nm Lidar System

Kong

Liu

Zhang

et al. 2018

Sensors

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In past decades, lidar techniques have become main tools for atmospheric remote sensing. However, traditional pulsed lidar systems are relatively expensive and require considerable maintenance. These shortcomings may be overcome by the development of a blue band Scheimpflug lidar system in Dalian, Northern China. Atmospheric remote measurements were carried out for 10 days in an urban area to validate the feasibility and performance of a 450-nm Scheimpflug lidar system. A 24-h continuous measurement was achieved in winter on a near horizontal path with an elevation angle of about 6.4°. The aerosol extinction coefficient retrieved by the Fernald-inversion algorithm shows good agreement with the variation of PM10/PM2.5 concentrations recorded by a national pollution monitoring station. The experimental result reveals that the linear ratio between the aerosol extinction coefficient and the PM10 concentration under high relative humidity (75–90%) is about two-times that in low relative humidity (≤75%) when the PM10 concentrations are less than 100 µg/m3.

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Section: Methodsmentioning

confidence: 99%

Atmospheric Pollution Monitoring in Urban Area by Employing a 450-nm Lidar System

Kong

Liu

Zhang

et al. 2018

Sensors

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“…The backscattering image of the laser beam propagating in the atmosphere and the background image with the laser diode turned off can then be alternately recorded, from which the raw lidar signal and the background signal can be retrieved, respectively. The final lidar curve was obtained after background subtraction, signal averaging, digital filtering with the Savitzky-Golay filter, and pixel-distance calibration by measuring the backscattering echo from the wall of a distant tall building (2.3 km away in this work) [53].…”

Section: The Scheimpflug Lidar Systemmentioning

confidence: 99%

Experimental Calibration of the Overlap Factor for the Pulsed Atmospheric Lidar by Employing a Collocated Scheimpflug Lidar

Mei

Zhang

et al. 2020

Remote Sensing

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Lidar techniques have been widely employed for atmospheric remote sensing during past decades. However, an important drawback of the traditional atmospheric pulsed lidar technique is the large blind range, typically hundreds of meters, due to incomplete overlap between the transmitter and the receiver, etc. The large blind range prevents the successful retrieval of the near-ground aerosol profile, which is of great significance for both meteorological studies and environmental monitoring. In this work, we have demonstrated a new experimental approach to calibrate the overlap factor of the Mie-scattering pulsed lidar system by employing a collocated Scheimpflug lidar (SLidar) system. A calibration method of the overlap factor has been proposed and evaluated with lidar data measured in different ranges. The overlap factor, experimentally determined by the collocated SLidar system, has also been validated through horizontal comparison measurements. It has been found out that the median overlap factor evaluated by the proposed method agreed very well with the overlap factor obtained by the linear fitting approach with the assumption of homogeneous atmospheric conditions, and the discrepancy was generally less than 10%. Meanwhile, simultaneous measurements employing the SLidar system and the pulsed lidar system have been carried out to extend the measurement range of lidar techniques by gluing the lidar curves measured by the two systems. The profile of the aerosol extinction coefficient from the near surface at around 90 m up to 28 km can be well resolved in a slant measurement geometry during nighttime. This work has demonstrated a great potential of employing the SLidar technique for the calibration of the overlap factor and the extension of the measurement range for pulsed lidar techniques.

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“…The final lidar signal is then obtained by taking the statistic median value of a number of signals to suppress the temporal noise such as the sunlight shot noise, readout noise and the dark current shot noise, etc. The exposure time of the CMOS sensor automatically changes according to the intensity of the background signal in order to optimize the SNR [41]. Meanwhile, the averaging number also changes correspondingly to maintain the same total measurement time for each single lidar curve, e.g., all lidar signals have been averaged 45 s for static measurements.…”

Section: Signal Acquisition and Processingmentioning

confidence: 99%

“…According to the Scheimpflug principle, the range resolution of the Scheimpflug lidar system in the near range is extraordinarily high, while it decreases rapidly with the measurement distance, as shown later in Figure 3. Thus, signal resampling is also performed for the near range lidar signals (<700 m) [41], and the range resolution is reduced to about 3 m in this region. Nevertheless, the lidar signals were still unequally sampled.…”

Section: Signal Acquisition and Processingmentioning

confidence: 99%

“…In other words, Remote Sens. 2019, 11, 837 7 of 15 the total incident light intensity should be at least more than 10% of the full-well intensity in order to minimize the noise resulting from the PRNU of the image sensor [41]. Typical exposure time is 20 ms under full sunny weather condition and 500 ms for complete darkness.…”

Section: Atmospheric Horizontal Scanning Measurements For Pollution Smentioning

confidence: 99%

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Preliminary Studies on Atmospheric Monitoring by Employing a Portable Unmanned Mie-Scattering Scheimpflug Lidar System

Zhi

et al. 2019

Remote Sensing

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A portable unmanned Mie-scattering Scheimpflug lidar system has been designed and implemented for atmospheric remote sensing. The Scheimpflug lidar system employs a continuous-wave high-power 808 nm laser diode as the light source and the emitted laser beam is collimated by an F6 lens with a 100 mm aperture. Atmospheric backscattering light is collected by a F5 lens with a 150 mm aperture and then detected by a 45° tilted image sensor. The separation between the transmitting and the receiving optics is about 756 mm to satisfy the Scheimpflug principle. Unmanned outdoor atmospheric measurements were performed in an urban area to investigate system performance. Localized emissions can be identified by performing horizontal scanning measurements over the urban atmosphere for 107° approximately every 17 min. The temporal variation of the vertical aerosol structure in the boundary layer has also been studied through zenith scanning measurements. The promising result shows great potential of the present portable lidar system for unmanned atmospheric pollution monitoring in urban areas.

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Noise modeling, evaluation and reduction for the atmospheric lidar technique employing an image sensor

Cited by 33 publications

References 29 publications

Atmospheric Pollution Monitoring in Urban Area by Employing a 450-nm Lidar System

Atmospheric Pollution Monitoring in Urban Area by Employing a 450-nm Lidar System

Experimental Calibration of the Overlap Factor for the Pulsed Atmospheric Lidar by Employing a Collocated Scheimpflug Lidar

Preliminary Studies on Atmospheric Monitoring by Employing a Portable Unmanned Mie-Scattering Scheimpflug Lidar System

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