Infrared Imaging Fourier Transform Spectrometer as the Stand-Off Gas Detection System

2011 ◽  
Vol 18 (4) ◽  
pp. 607-620 ◽  
Author(s):  
Mariusz Kastek ◽  
Tadeusz Piątkowski ◽  
Piotr Trzaskawka

Infrared Imaging Fourier Transform Spectrometer as the Stand-Off Gas Detection SystemThe article presents the detection of gases using an infrared imaging Fourier-transform spectrometer (IFTS). The Telops company has developed the IFTS instrumentHyperCam, which is offered as a short- or long-wave infrared device. The principle ofHyperCamoperation and methodology of gas detection has been shown in the paper, as well as theoretical evaluation of gas detection possibility. Calculations of the optical path between the IFTS device, cloud of gases and background have been also discussed. The variation of a signal reaching the IFTS caused by the presence of a gas has been calculated and compared with the reference signal obtained without the presence of a gas in IFTS's field of view. Verification of the theoretical result has been made by laboratory measurements. Some results of the detection of various types of gases has been also included in the paper.

2021 ◽  
Author(s):  
Erik Kretschmer ◽  
Felix Friedl-Vallon ◽  
Thomas Gulde ◽  
Michael Höpfner ◽  
Sören Johansson ◽  
...  

<p>The GLORIA-B (Gimballed Limb Observer for Radiance Imaging of the Atmosphere - Balloon) instrument is an adaptation of the very successful GLORIA-AB imaging Fourier transform spectrometer (iFTS) flown on the research aircrafts HALO and M55 Geophysica. The high spectral resolution in the LWIR (Long Wave Infrared) allows for the retrieval of temperature and of a broad range of atmospheric trace gases, with the goal to retrieve O<sub>3</sub>, H<sub>2</sub>O, HNO<sub>3</sub>, C<sub>2</sub>H<sub>6</sub>, C<sub>2</sub>H<sub>2</sub>, HCOOH, CCl<sub>4</sub>, PAN, ClONO<sub>2</sub>, CFC-11, CFC-12, SF<sub>6</sub>, OCS, NH<sub>3</sub>, HCN, BrONO<sub>2</sub>, HO<sub>2</sub>NO<sub>2</sub>, N<sub>2</sub>O<sub>5</sub> and NO<sub>2</sub>. The radiometric sensitivity of the Balloon instrument is further increased in comparison with the GLORIA-AB instrument by having two detector channels on the same focal plane array, while keeping the same concept of a cooled optical system. This system improvement was achieved with minimal adaptation of the existing optical system.</p><p>The high spatial and temporal resolution of the instrument is ensured by the imaging capability of the Fourier transform spectrometer while stabilizing the line-of-sight in elevation with the instrument and in azimuth with the balloon gondola. In a single measurement lasting 13 seconds, the atmosphere can be sounded from mid-troposphere up to flight altitude, typically 30 km, with a vertical resolution always better than 1 km for most retrieved species; a spatial resolution up to 0.3 km can be achieved in favourable conditions. Temperature retrieval precision between 0.1 and 0.2 K is expected. A spectral sampling up to 0.0625 cm<sup>-1</sup> can be achieved.</p><p>The first flight of GLORIA-B shall take place during the late-summer polar jet turn-around at Kiruna/ESRANGE. This flight is organised in the frame of the HEMERA project and was scheduled for summer 2020, but was ultimately postponed to summer 2021. Beyond qualification of the first balloon-borne iFTS, the scientific goals of the flight are, among others, the quantification of the stratospheric bromine budget and its diurnal evolution by measuring vertical profiles of BrONO<sub>2 </sub>in combination with BrO observations by the DOAS instrument of University Heidelberg on the same platform.</p>


Author(s):  
Mohit Dua ◽  
Abhinav Mudgal ◽  
Mukesh Bhakar ◽  
Priyal Dhiman ◽  
Bhagoti Choudhary

In this chapter, a human detection system based on unsupervised learning method K-means clustering followed by deep learning approach You Only Look Once (YOLO) on thermal imagery has been proposed. Generally, images in the visible spectrum are used to conduct such human detection, which are not suitable for nighttime due to low visibility, hence for evaluation of our system. Hence, long wave infrared (LWIR) images have been used to implement the proposed work in this chapter. The system follows a two-step approach of generating anchor boxes using K-means clustering and then using those anchor boxes in 252 layered single shot detector (YOLO) to predict proper boundary boxes. The dataset of such images is provided by FLIR company. The dataset contains 6822 images for training purposes and 757 images for the validation. This proposed system can be used for real-time object detection as YOLO can achieve much higher rate of processing when compared to traditional method like HAAR cascade classifier in long wave infrared imagery (LWIR).


2019 ◽  
Vol 48 (6) ◽  
pp. 611004
Author(s):  
闫羽 YAN Yu ◽  
徐小红 XU Xiao-hong ◽  
范之国 FAN Zhi-guo ◽  
张强 ZHANG Qiang ◽  
金海红 JIN Hai-hong

1997 ◽  
Vol 68 (1) ◽  
pp. 30-33 ◽  
Author(s):  
D. Steers ◽  
B. A. Patterson ◽  
W. Sibbett ◽  
M. J. Padgett

2017 ◽  
Vol 25 (19) ◽  
pp. 22440 ◽  
Author(s):  
Liyin Yuan ◽  
Zhiping He ◽  
Gang Lv ◽  
Yueming Wang ◽  
Chunlai Li ◽  
...  

2014 ◽  
Vol 39 (16) ◽  
pp. 4911 ◽  
Author(s):  
WenCong Wang ◽  
JingQiu Liang ◽  
ZhongZhu Liang ◽  
JinGuang Lü ◽  
YuXin Qin ◽  
...  

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