Spectroscopic measurements of infrared CO2 transitions in gas plumes are reported, and evaluated for their potential to yield a reliable remote sensing technique for determination of plume temperature. Measurments were made on two types of plumes: a sideways-directed plume from a vehicle exhaust, and a stack plume from a propane-burning portable plume generator. Modeling of CO2 emission near 4.25 μm from the portable plume generator does not yield a temperature diagnostic due to heavy and unpredictable atmospheric absorption. The 4.25 μm band is optically thick in the vehicle exhaust plume measurements. For the vehicle plume, the blackbody Planck equation is used to derive temperatures that agree with results of thermocouple measurements. The ratio of optically thin signals obtained in the vicinity of the 4.25 μm and 14.4 μm transitions is related to temperature in accordance with Boltzmann statistics. For these experimental conditions, the ratio calculated from the Boltzmann distribution has similar temperature dependence to the ratio obtained from the blackbody Planck equation. Because the ratio of signals obtained at two optically thin wavelengths is independent of concentration, this technique has promise for field measurement of plume temperatures.
Using a Fourier transform infrared field spectrometer, spectral infrared radiance measurements were made of several generated gas plumes against both a uniform sky and terrestrial background. Background temperature, spectral complexity, and physical homogeneity each influenced the success of emissive infrared spectral sensing technology in detecting and identifying the presence of a gas plume and its component constituents. As expected, high temperature contrast and uniform backgrounds provided the best conditions for detectibility and diagnostic identification. This report will summarize some of SITAC's findings concerning plume detectability, including the importance of plume cooling, plumes in emission and absorption, the effects of optical thickness, and the effects of condensing plumes on gas detection.
Spectral infrared emissivity measurements have been made of a variety of materials both with and without surface water. The surface water was either natural, in the form of dew or residual rainwater, or artificially introduced by manual wetting. Materials naturally high in water content were also measured. Despite the rather diverse spectral population of the underlying materials, they exhibited very similar, featureless, water-like spectra; spectrally flat with a very high magnitude across the emissive infrared region. The implication to exploitation personnel that may use emissive infrared hyperspectral image data is that in areas where condensation is likely (e.g. high humidity) or in areas populated with high water content background materials (e.g. highly vegetated areas), discrimination may prove an intractable problem with hyperspectral infrared sensing for ambient temperature targets. A target that exhibits a temperature either below or above ambient temperature may be detectable, but not identified, and may be more economically pursued with a far simpler, single-band midwave or longwave sensor.
Spectra were taken that describes free water, ice, and snow, and vegetation and inorganic backgrounds. The reflectance of water films, ranging from 0.008 to 5.35 mm, on a spectralon background varied with water depth and the water transmittance and absorbtance properties. Thin water films, > 3.5 mm, quenched the short wave infrared (SWIR) reflectance, even though moderate visible-near infrared reflectance occurred from the water-spectralon surfaces. Ice and snow have a similar number of absorption bands as water but their absorption maxima varied from those of water. River float-ice and glacial ice have diagnostic absorption features at 1.02 and 1.25 μm and negligible reflectance in the > 1.33 μm region. New powder snow, new wet snow, and older deep snow packs have similar shaped reflectance spectra. Thin snow accumulations readily masked the underlying surfaces. These snow pack surfaces have a small asymmetric absorption features at 0.90 μm and strong asymmetric absorption features at 1.02, 1.25, and 1.50 μm. These snow packs have measurable SWIR reflectance. An avalanche snow pack had low SWIR reflectance, which was similar to ice spectra. Water, ice and snow and ice surfaces have spectrally distinct features, which differentiates them and the background surfaces.
A Michelson Fourier Transform Spectrometer senses an object/material in the time domain, producing an interferogram. To produce a spectrum, the interferogram is Fourier transformed into the spectral domain. Unless filtering is applied to the interferogram, all the time changing (AC) components of the interferogram contribute to the resulting spectrum. Aperiodic signals are not easily removed from the interferogram and, when transformed, result in false spectral features. Possible sources of real-world aperiodic signals are discussed and their effects on the resulting transformed spectra are demonstrated. Mitigation and avoidance techniques for some of the more common real- world aperiodic signals are discussed.
Conference Committee Involvement (4)
Active and Passive Signatures IV
1 May 2013 | Baltimore, Maryland, United States
Active and Passive Signatures III
25 April 2012 | Baltimore, Maryland, United States
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.