ShipIR model validation using spectral measurement results from the NATO SIMVEX trial

Brendhagen, Erik; Heen, Lars Trygve

doi:10.1117/12.485859

Cited by 6 publications

(5 citation statements)

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“…However, the trends that we observe, the decay of the observed radiance contrast with distance, are clear. The composition of the gas/soot mixture and its temperature that are used in the FASCODE modeling are chosen in such a way that the observed spectral radiance corresponds to the observed spectrum as measured with a Fourier Transform IR Spectrometer at relative short range (1 km) [3]. Although the mixture and temperature was adjusted for one particular ship, it is believed that the decay constants are not very sensitive to mixture composition.…”

Section: Discussionmentioning

confidence: 99%

Comparison of distance dependence of ship signature and intensity of ship exhaust gas measured in both MWIR and LWIR transmission bands

2009

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A ship's exhaust gas contains both hot gas molecules, which emit infrared radiation at specific wavelengths (line emitters), and soot particles which emit broad-banded, like a black body. Our modeling shows that the observed radiance from these emissions falls at different rates with distance. The attenuation of intensity is caused by absorption and scattering of the emitted radiation in the atmosphere. The hottest part of the exhaust plume is spatially confined to a relative small volume. Usually, a ship's hull and its superstructure have a higher temperature than the sky or sea background. The temperature difference is generally not very large. However, the ship has a spatial extent that is much larger than the plume's. In this work we study how both the emitted radiation from the plume and the ship's total signature decrease with increasing distance. This study is based on experimental data that was collected during a measurement campaign at the southwest coast of Norway. Shore-based digital IR cameras, both LWIR and MWIR, recorded image sequences of ships as they sailed away from close to shore (~ 1 km) in a zigzag pattern out to about 10 km. We used a statistical method to identify the gas cloud pixels and used their integrated radiance as a measure for the plume intensity. The ship signature is defined here as the integrated radiance over all the ship's pixels in the imagery. From infrared spectroscopic data, collected using a Fourier Transform Infrared spectrometer aimed at the ship's plume when the ship is close to shore, a model is obtained for the composition of the exhaust gas. This model was used to perform FASCODE simulations to study numerically the attenuation with distance of the plume radiance. Our work shows that this approach may be well suited to explain the observed signal decay rate with distance.

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Section: Discussionmentioning

confidence: 99%

Comparison of distance dependence of ship signature and intensity of ship exhaust gas measured in both MWIR and LWIR transmission bands

2009

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“…Temperature analyses were performed for nine runs, and IR analyses were performed for 10 runs. Norway performed spectral measurements during the plume runs (and also made spectral measurements of the ship and background); these results will be presented in a separate paper [8]. The U.S. team's analysis focused on V3.0, both MWIR and LWIR bands, and daytime runs (both clear and cloudy).…”

Section: Validation Resultsmentioning

confidence: 99%

“…Figure 6 compares ship surface temperature. The runs are grouped into day runs (8,14,19, and 32) and night runs (15, 16, 20, 21, and 34). For the combined set of day and night runs, the overall root-mean-square (RMS) temperature prediction error is 2.6 °C.…”

Section: Validation Resultsmentioning

confidence: 99%

ShipIR model validation using NATO SIMVEX experiment results

et al. 2003

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Standard Form 298 (Rev. 8-98)Prescribed by ANSI Std. Z39.18Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing this collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden to Department of Defense, Washington Headquarters Services, Directorate for Information Operations and Reports (0704-0188), 1215 Jefferson Davis Highway, Suite 1204, Arlington, VA 22202-4302. Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to any penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS.

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“…This method is applicable both for solid materials and gas clouds, but generally gas clouds have stronger variations in spectral infrared radiation. [1] …”

Section: Introductionmentioning

confidence: 97%

Obtaining spectral information from infrared scenarios using hyper-spectral cameras and cameras with spinning filter wheel

Glimsdal

Brendhagen

Thomassen

et al. 2014

Electro-Optical Remote Sensing, Photonic Technologies, and Applications VIII; And Military Applications in Hyperspectral Imagin

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In the past decades the Norwegian Defence Research Establishment (FFI) has recorded and characterized infrared scenarios for several application purposes, such as infrared target and background modeling and simulation, model validation, atmospheric propagation, and image segmentation and target detection for civilian and defence purposes. During the last year FFI has acquired several new systems for characterization of infrared radiation properties. In total, five new infrared cameras from IRCAM GmbH, Germany, have been acquired. These cameras cover both the longwavelength and extended medium-wavelength infrared spectral bands. The cameras are equipped with fast rotating filter wheels which can be used to study spectral properties and polarization effects within these wavelength bands. This option allows the sensors to operate in user-defined spectral bands. FFI has also acquired two HyperCam sensors from Telops Inc, Canada, covering the long-wavelength and extended medium-wavelength spectral bands, respectively. The combination of imaging detectors and Fourier Transform spectroscopy allows simultaneous spectral and spatial characterization of infrared scenarios. These sensors may optionally be operated as high-speed infrared cameras. A description of the new sensors and their capabilities are presented together with some examples of results acquired by the different sensors. In this paper we present a detailed comparison of images taken in different spectral bands, and also compare images taken with the two types of sensors. These examples demonstrate the principles of how the new spectral information can be used to separate certain targets from the background based on the spectral information.

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ShipIR model validation using spectral measurement results from the NATO SIMVEX trial

Cited by 6 publications

References 0 publications

Comparison of distance dependence of ship signature and intensity of ship exhaust gas measured in both MWIR and LWIR transmission bands

Comparison of distance dependence of ship signature and intensity of ship exhaust gas measured in both MWIR and LWIR transmission bands

ShipIR model validation using NATO SIMVEX experiment results

Obtaining spectral information from infrared scenarios using hyper-spectral cameras and cameras with spinning filter wheel

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