Adaptive Detection Algorithm for Hazardous Clouds Based on Infrared Remote Sensing Spectroscopy and the LASSO Method

Li, Dacheng; Fangxiao, Cui; Wang, Anjing; Li, Yangyu; Wu, Jun; Qiao, Yang

doi:10.1109/tgrs.2020.2989526

Cited by 4 publications

(4 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…扫描傅里叶变换红外(FTIR)遥测成像技术 [1][2][3] 是具有空间和光谱维度探测能力的一种新型气体成像技术，它具有远距离、非接触式采样、高灵敏度和高分辨率等优点，对于化工园区定点 360 度覆盖式气体泄漏常态化监测具有极大的应用价值。扫描 FTIR 遥测成像技术在对场景目标成像过程中，由于仪器架设位置和 2 目标监测区域的高度等因素，经常出现扫描像素对应的红外背景来自天空辐射，天空红外背景具有冷空特性，且各种大气分子具有程长辐射累积特征 [4] ，因此与近地面的被测目标成分有较大的温差，也使得从实测天空红外辐射中提取目标特征的难度加大。在扫描 FTIR 遥测成像系统对目标的常态化监测过程中，获取背景光谱是对目标气体特征提取、识别和定量分析 [5][6][7] 的前提条件，目前有多种背景提取方法可供参考或应用。Theriault [8] 提出了测量同等条件下干净背景谱的方法，该方法简单有效，但在复杂场景下的实用性和实时性低。Dennis [9] 和 Wayne [10] 分别采用中分辨率大气辐射传输模型(MODTRAN)和快速大气信息程序(FASCODE)根据测量环境模拟生成了背景光谱，该方法可确保仿真背景的纯净性，但仅能模拟低仰角下的天空背景且实时性低。高闽光 [11] 提出了测量热烟羽上风口背景谱的方法，该方法对时间和空间临近要求很高。Harig [12,13] 认为被测气体特征是线性叠加在背景光谱上的，通过目标、干扰物和背景基线拟合测量谱来提取气体特征，这种方法的时间复杂度低，具有良好的实时性，但标准光谱仅能够仿真设定的大气状态和观测参数。焦阳 [2] 通过实测光谱实时提取背景的方法反演被测污染气体透过率，该方法只适用于低平天空或对地观测。李大成 [14] 使用 ECMWF 廓线 [15] 计算低仰角(小于 35°)下各种大气条件的光谱特征，利用 Lasso 算法 [16] 进行快速特征优选，选择最优目标与背景组合重构测量光谱，以提取目标特征，该方法实时性较高，然而相比于短时间临近区域的实测背景依然存在较大差异，此外还需要建立包含各类场景的背景库。上述背景提取算法对于单点测量或小范围内探测具有良好的效果，然而对于具有复杂工业环境、大范围成像监测等情况 [17] 适用程度极低。含量之间存在近似的线性关系 [4] 。综上考虑，温度廓线与湿度廓线是红外向下辐射需要考虑的首要因素。 MODTRAN [18,20] 噪声 RMS 的五倍，误警率则低至 1/500000 [18,20] 。从表 3 可知，插值生成的背景…”

Section: 引言unclassified

Inversion method of target gas cloud transmittance based on atmospheric profile synthesis background

Yun-you¹,

Xu²,

Shen³

et al. 2023

Acta Phys. Sin.

View full text Add to dashboard Cite

The sky infrared background radiation varies greatly with spatial distribution and time. When Scanning Fourier Transform Infrared (FTIR) remote sensing imaging system scans the target gas cloud with the sky as the background, the background radiation corresponding to each scanned pixel is different, and the background does not have a constant baseline. It is extremely difficult to obtain the background spectrum of each pixel in real-time, which affects the inversion accuracy of the target gas cloud transmittance. An inversion method of target gas cloud transmittance based on atmospheric profile synthesis background is proposed. The temperature, humidity, pressure, and ozone profiles of the measured locations and the atmospheric model are used to generate the sky infrared background in order to solve the problem that it is difficult to measure the clean sky infrared background spectrum in the chemical industry park. This paper proposes that there is a continuous derivable relationship between the sky infrared background spectrum and the cosine of zenith angle at each wavenumber, so a small amount of sky infrared background spectrum with a zenith angle gradient can quickly generate sky infrared background spectrum at any elevation angle. The proposed method is verified by the Moderate Resolution Atmospheric Radiative Transfer Model (MODTRAN) software simulation and the remote sensing imaging experiment of SF<sub>6</sub> gas. The proposed method can quickly generate the sky infrared background spectrum corresponding to any angle within the gradient elevation angle and accurately invert the target gas cloud transmittance at each pixel. The results show that the distribution trend of the column concentration of the SF<sub>6</sub> gas cloud is consistent with the actual distribution, the correlation is 0.99979.

show abstract

Section: 引言unclassified

Inversion method of target gas cloud transmittance based on atmospheric profile synthesis background

Yun-you¹,

Xu²,

Shen³

et al. 2023

Acta Phys. Sin.

View full text Add to dashboard Cite

show abstract

“…Passive Fourier transform remote sensing technology enables the detection and identification of chemical pollutants in the air [1], and has been widely studied and applied in many fields such as the detection of hazardous clouds [2][3][4][5][6][7], the analysis of aircraft exhaust plume [8][9][10], pollution gas emissions over distance monitoring [11][12][13][14][15] and taking measurements of greenhouse gases [16][17][18]. The Fourier transform infrared spectrometer is mainly carried by a vehicle or fixed on a tripod which is slow to deploy or requires dedicated runways [19].…”

Section: Introductionmentioning

confidence: 99%

“…The external calibration requires strict environmental conditions for the UAV-integrated system applied in the field. Li et al used the least absolute shrinkage and selection operator (LASSO) method to select the most appropriate reference for spectral fitting [7]. The accuracy of fitting decreases when the atmospheric state changes due to poor meteorological conditions or the turbulence effects associated with the complex air flow around a UAV.…”

Section: Introductionmentioning

confidence: 99%

Unmanned Helicopter Airborne Fourier Transform Infrared Spectrometer Remote Sensing System for Hazardous Vapors Detection

Shi,

Huang,

Qian

et al. 2024

Applied Sciences

View full text Add to dashboard Cite

The rapid development of unmanned aerial vehicles (UAVs) provides a new application mode for gas remote sensing. Compared with fixed observation and vehicle-mounted platforms, a Fourier transform infrared spectrometer (FTIR) integrated in the UAV can monitor chemical gases across a large area, can collect data from multiple angles in three-dimensional space, and can operate in contaminated or hazardous environments. The unmanned helicopter has a larger payload and longer endurance than the rotary-wing drone, which relaxes the weight, size and power consumption limitations of the spectrometer. A FTIR remote sensing system integrated in an unmanned helicopter was developed. In order to solve the data acquisition and analysis problem caused by vibration and attitude instability of the unmanned helicopter, a dual-channel parallel oscillating mirror was designed to improve the stability of the interferometer module, and a robust principal component analysis algorithm based on kernel function was used to separate background spectrum and gas features. The flight experiment of sulfur hexafluoride gas detection was carried out. The results show that the system operates stably and can collect and identify the target spectrum in real time under the motion and hovering modes of an unmanned helicopter, which has broad application prospects.

show abstract

“…Additionally, the accurate classification of the specific chemical gas present in the atmosphere is crucial, as the approach to handling these gases varies with their types. Recognizing the significance of swift responses to chemical threats, researchers have focused on leveraging Fourier transform infrared (FTIR) spectroscopy [ 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 ]. This technique allows for the remote and non-contact analysis of materials.…”

Section: Introductionmentioning

confidence: 99%

Semi-Supervised Autoencoder for Chemical Gas Classification with FTIR Spectrum

Jang,

Kwon,

Nam

et al. 2024

Sensors

View full text Add to dashboard Cite

Chemical warfare agents pose a serious threat due to their extreme toxicity, necessitating swift the identification of chemical gases and individual responses to the identified threats. Fourier transform infrared (FTIR) spectroscopy offers a method for remote material analysis, particularly in detecting colorless and odorless chemical agents. In this paper, we propose a deep neural network utilizing a semi-supervised autoencoder (SSAE) for the classification of chemical gases based on FTIR spectra. In contrast to traditional methods, the SSAE concurrently trains an autoencoder and a classifier attached to a latent vector of the autoencoder, enhancing feature extraction for classification. The SSAE was evaluated on laboratory-collected FTIR spectra, demonstrating a superior classification performance compared to existing methods. The efficacy of the SSAE lies in its ability to generate denser cluster distributions in latent vectors, thereby enhancing gas classification. This study established a consistent experimental environment for hyperparameter optimization, offering valuable insights into the influence of latent vectors on classification performance.

show abstract

Adaptive Detection Algorithm for Hazardous Clouds Based on Infrared Remote Sensing Spectroscopy and the LASSO Method

Cited by 4 publications

References 22 publications

Inversion method of target gas cloud transmittance based on atmospheric profile synthesis background

Inversion method of target gas cloud transmittance based on atmospheric profile synthesis background

Unmanned Helicopter Airborne Fourier Transform Infrared Spectrometer Remote Sensing System for Hazardous Vapors Detection

Semi-Supervised Autoencoder for Chemical Gas Classification with FTIR Spectrum

Contact Info

Product

Resources

About