Telops has a 20-year history in the design, construction, and deployment of thermal infrared hyperspectral imaging systems through the legacy Hyper-Cam line. Advances in critical subsystem technologies has allowed Telops to develop the next-generation of hyperspectral imaging systems with significant reductions in size, weight, and power requirements while maintaining imaging and data quality performance. This reduction in SWaP requirements yields a significant increase in deployment flexibility, allowing for increased capability for collecting actionable hyperspectral data of remote or difficult-to-access targets. Also taking benefit of the most recent data processing capabilities from modern electronics and computer systems, the real-time data analysis has enabled unprecedented ease of use and conviviality without compromise to performance. This presentation will serve as an overview of the system architecture and analysis capabilities of three next-generation thermal infrared hyperspectral imaging products. These platforms include a tripod-based system for ground measurements; an airborne platform designed for small, fixed-wing aircraft; and a small-footprint system designed for deployment on a quadcopter or other small UAV.
Detection, identification, and quantification of exhaust gas emissions is critical to ensure compliance with regulatory guidelines and mitigate damage to the environment. Passive thermal infrared hyperspectral imaging is among the technical solutions that can remotely detect, identify, and quantify multiple gases simultaneously. Telops has recently developed a suite of gas quantification tools designed for use on the Hyper-Cam series of hyperspectral imaging systems. In order to demonstrate the feasibility of quantitative gas measurements in real-world environments, Telops participated in a maritime measurement campaign in 2021. The Telops Hyper-Cam-LW was used to quantitatively measure the SO2 emissions from the main exhaust of a cargo ship transiting the Saint Lawrence Seaway. This work will introduce the fundamental principles underlying gas quantitation using thermal infrared hyperspectral imaging as well as report quantitative gas imaging results generated from the 2021 measurement campaign.
Detection, identification, and quantification of greenhouse gases is essential to ensure compliance with regulatory guidelines and mitigate damage associated with anthropogenic climate change. Passive infrared hyperspectral imaging technology is among the solutions that can detect, identify and quantify multiple greenhouse gases simultaneously. The Telops Hyper-Cam Airborne Platform is an established system for aerial thermal infrared hyperspectral measurements for gas survey applications. In support of the Hypercam, Telops is developing a suite of hyperspectral imaging data processing algorithms that allow for gas detection, identification, and quantification in real-time. In the Fall of 2020, the Hyper-Cam-LW Airborne platform was flown above a validated SF6 gas release system to collect hyperspectral data for gas quantification analysis. This measurement campaign was performed to document performance of the Hyper-Cam gas quantification capabilities against known quantities of released gas. This talk introduces the principles behind the gas detection, identification, and quantification algorithms and presents the motivations and results from the Fall 2020 measurement campaign.
Characterization of ship plumes is very challenging due to the great variety of ships, fuel, and fuel grades, as well as the extent of a gas plume. In this work, imaging of ship plumes from an operating ferry boat was carried out using standoff midwave (3-5 μm) infrared hyperspectral imaging. Quantitative chemical imaging of combustion gases was achieved by fitting a radiative transfer model. Combustion efficiency maps and mass flow rates are presented for carbon monoxide (CO) and carbon dioxide (CO2). The results illustrate how valuable information about the combustion process of a ship engine can be successfully obtained using passive hyperspectral remote sensing imaging.
Characterization of ship plumes is very challenging due to the great variety of ships, fuel, and fuel grades, as well as the extent of a gas plume. In this work, imaging of ship plumes from an operating ferry boat was carried out using standoff midwave (3-5 μm) infrared hyperspectral imaging. Quantitative chemical imaging of combustion gases was achieved by fitting a radiative transfer model. Combustion efficiency maps and mass flow rates are presented for carbon monoxide (CO) and carbon dioxide (CO2). The results illustrate how valuable information about the combustion process of a ship engine can be successfully obtained using passive hyperspectral remote sensing imaging.
Characterization of hazardous lands using ground-based techniques can be very challenging. For this reason, airborne
surveys are often preferred. The use of thermal infrared imaging represents an interesting approach as surveys can be
carried out under various illumination conditions and that the presence of buried objects typically modifies the thermal
inertia of their surroundings. In addition, the burial or presence of a buried object will modify the particle size, texture,
moisture and mineral content of a small region around it. All these parameters may lead to emissivity contrasts which will
make thermal contrast interpretation very challenging. In order to illustrate the potential of airborne thermal infrared
hyperspectral imaging for buried object characterization, various metallic objects were buried in a test site prior to an
airborne survey. Airborne hyperspectral images were recorded using the targeting acquisition mode, a unique feature of
the Telops Hyper-Cam Airborne system which allows recording of successive maps of the same ground area. Temperatureemissivity
separation (TES) was carried out on the hyperspectral map obtained upon scene averaging. The thermodynamic
temperature map estimated after TES highlights the presence of hot spots within the investigated area. Mineral mapping
was carried out upon linear unmixing of the spectral emissivity datacube obtained after TES. The results show how the
combination of thermal information and mineral distribution leads to a better characterization of test sites containing buried
objects.
Characterization of hazardous lands using ground-based techniques can be very challenging. For this reason, airborne surveys are often preferred. The use of thermal infrared imaging represents an interesting approach as surveys can be carried out under various illumination conditions and that the presence of buried objects typically modifies the thermal inertia of their surroundings. In addition, the burial or presence of a buried object will modify the particle size, texture, moisture and mineral content of a small region around it. All these parameters may lead to emissivity contrasts which will make thermal contrast interpretation very challenging. In order to illustrate the potential of airborne thermal infrared hyperspectral imaging for buried object characterization, various metallic objects were buried in a test site prior to an airborne survey. Airborne hyperspectral images were recorded using the targeting acquisition mode, a unique feature of the Telops Hyper-Cam Airborne system which allows recording of successive maps of the same ground area. Temperatureemissivity separation (TES) was carried out on the hyperspectral map obtained upon scene averaging. The thermodynamic temperature map estimated after TES highlights the presence of hot spots within the investigated area. Mineral mapping was carried out upon linear unmixing of the spectral emissivity datacube obtained after TES. The results show how the combination of thermal information and mineral distribution leads to a better characterization of test sites containing buried objects.
Persistent surveillance and collection of airborne intelligence, surveillance and reconnaissance information
is critical in today's warfare against terrorism. High resolution imagery in visible and infrared bands
provides valuable detection capabilities based on target shapes and temperatures. However, the spectral
resolution provided by a hyperspectral imager adds a spectral dimension to the measurements, leading to
additional tools for detection and identification of targets, based on their spectral signature. The Telops
Hyper-Cam sensor is an interferometer-based imaging system that enables the spatial and spectral analysis
of targets using a single sensor. It is based on the Fourier-transform technology yielding high spectral
resolution and enabling high accuracy radiometric calibration. It provides datacubes of up to 320×256
pixels at spectral resolutions as fine as 0.25 cm-1. The LWIR version covers the 8.0 to 11.8 μm spectral
range. The Hyper-Cam has been recently used for the first time in two compact airborne platforms: a belly-mounted
gyro-stabilized platform and a gyro-stabilized gimbal ball. Both platforms are described in this
paper, and successful results of high-altitude detection and identification of targets, including industrial
plumes, and chemical spills are presented.
There is growing interest in measuring gaseous emissions to understand their environmental impact. It is thus desired to
identify and quantify such emissions, ideally from standoff distances. AFIT and Telops have performed several field
experiments, using the Telops Hyper-Cam infrared hyperspectral imager to perform identification and quantification of
gaseous emissions from various pollution sources. Recent experiments have focused on turbulent gaseous emissions
from sources of great interest from the environmental protection community, such as emergency flares. It is important to
understand the flare emissions under varying operating conditions. This paper presents the first results of flare emission
measurements with the Hyper-Cam.
The Reststrahlen effect has been investigated for detecting regions of recently disturbed earth, by taking images where
metallic objects had been buried in a sandy soil and comparing with images of undisturbed soil. The images were taken
with a Long wave Infrared (LWIR) Hyperspectral Sensor, the Hyper-Cam.
The midwave and longwave infrared regions of the electromagnetic spectrum contain rich information which can be
captured by hyperspectral sensors thus enabling enhanced detection of targets of interest. A continuous hyperspectral
imaging measurement capability operated 24/7 over varying seasons and weather conditions permits the evaluation of
hyperspectral imaging for detection of different types of targets in real world environments. Such a measurement site
was built at Picatinny Arsenal under the Spectral and Polarimetric Imagery Collection Experiment (SPICE), where two
Hyper-Cam hyperspectral imagers are installed at the Precision Armament Laboratory (PAL) and are operated
autonomously since Fall of 2009. The Hyper-Cam are currently collecting a complete hyperspectral database that
contains the MWIR and LWIR hyperspectral measurements of several targets under day, night, sunny, cloudy, foggy,
rainy and snowy conditions.
The Telops Hyper-Cam sensor is an imaging spectrometer that enables the spatial and spectral analysis capabilities using
a single sensor. It is based on the Fourier-transform technology yielding high spectral resolution and enabling high
accuracy radiometric calibration. It provides datacubes of up to 320x256 pixels at spectral resolutions of up to 0.25 cm-1.
The MWIR version covers the 3 to 5 μm spectral range and the LWIR version covers the 8 to 12 μm spectral range.
This paper describes the automated operation of the two Hyper-Cam sensors being used in the SPICE data collection.
The Reveal Automation Control Software (RACS) developed collaboratively between Telops, ARDEC, and ARL
enables flexible operating parameters and autonomous calibration. Under the RACS software, the Hyper-Cam sensors
can autonomously calibrate itself using their internal blackbody targets, and the calibration events are initiated by user
defined time intervals and on internal beamsplitter temperature monitoring. The RACS software is the first software
developed for COTS hyperspectal sensors that allows for full autonomous data collection capability for the user. The
accuracy of the automatic calibration was characterized and is presented in this paper.
The midwave and shortwave infrared regions of the electromagnetic spectrum contain rich information enabling the characterization of hot, rapid events such as explosions, engine plumes, flares and other combustion events. High-speed sensors are required to analyze the content of such rapidly evolving targets. Cameras with high frame rates and non-imaging spectrometers with high data rates are typically used; however the information from these two types of instruments must be later fused to enable characterization of the transient targets. Imaging spectrometers have recently become commercially available for general scientific use, thus enabling simultaneous capture of both spatial and spectral information without co-registration issues. However, their use against rapidly-varying sources has traditionally been considered problematic, for even at moderate spatial and spectral resolutions the time to acquire a single spectrum can be long compared to the timescales associated with combustion events.
This paper demonstrates that imaging Fourier-transform spectroscopy (IFTS) can successfully characterize the turbulent combustion exhaust from a turbojet engine. A Telops Hyper-Cam IFTS collected hyperspectral video from a Turbine Technologies SR-30 turbojet engine with a spectral resolution of δν = 1/cm-1 on a 200×64 pixel sub-window at a rate of 0.3 Hz. Scene-change artifacts (SCAs) are present in the spectra; however, the stochastic fluctuations in source intensity translate into high-frequency "noise." Temporal averaging affords a significant reduction of the noise associated with SCAs. Emission from CO and CO2 are clearly recognized in the averaged spectra, and information about their temperature and relative concentrations is evident.
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