Thermal multispectral detection of military vehicles in vegetated and desert backgrounds

Schwartz, Craig R.; Eismann, Michael T.; Cederquist, Jack N.; Johnson, Ray O.

doi:10.1117/12.243007

Cited by 18 publications

(9 citation statements)

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“…In particular the approach of ERIM [2] will be investigated on this data. All of the analysis carried out in this paper is based on linear techniques.…”

Section: Hyperspectral Algorithm Development Workmentioning

confidence: 99%

“…All of the analysis carried out in this paper is based on linear techniques. The approach in [2] is based on the assumption that natural backgrounds have statistical properties that can be described by a multivariate Gaussian. Extension of these ideas to non-Gaussian statistics in a natural way will be discussed in [3] where some results on the SPIRIT data will be presented.…”

Section: Hyperspectral Algorithm Development Workmentioning

confidence: 99%

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<title>SPIRIT: a hyperspectral infrared imager</title>

Evans¹,

Hargreaves²,

Evans³

et al. 1999

SPIE Proceedings

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The SPIRIT system is a spectrally agile infra-red imaging airborne camera, with the capability to select any of the multiple (narrow band) filters on a frame by frame basis. The implemented solution employs advanced, but proven, technology to meet the objectives, and achieved good spatial and thermal performance in all modes. Sophisticated electronic design has resulted in a flexible unit, which can respond to the changing requirements of the user. Initial SPIRIT flight trials were undertaken in summer 1998 with more scheduled to continue through 1999. The sensor was installed on to DERA's TIARA research platform, a modified Tomado F2. The flight trials to date have been conducted over a variety of scenarios, collecting spectral data in up to 12 bands, of other aircraft, tanks, and fixed targets. Further ground-based trials, with the sensor mounted on a pan and tilt tracking platform, have been performed on characterised targets and against further air targets. Data from these initial trials are currently being processed to assess whether sufficient spectral information is available to discriminate between target types at militarily significant ranges. Sample hyperspectral imagery from SPIRIT and some results are presented.

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“…In particular the approach of ERIM [2] will be investigated on this data. All of the analysis carried out in this paper is based on linear techniques.…”

Section: Hyperspectral Algorithm Development Workmentioning

confidence: 99%

Section: Hyperspectral Algorithm Development Workmentioning

confidence: 99%

<title>SPIRIT: a hyperspectral infrared imager</title>

Evans¹,

Hargreaves²,

Evans³

et al. 1999

SPIE Proceedings

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“…The COBRA RX mine detection algorithm result (referred to as RX value), computed at each image pixel, is a multiband spectrallspatial anomaly detection metric [3,4,5,6,7]. It is a measure of the multi-band signal-to-clutter-ratio (SCR) of objects with a contrasting spectral response from the background.…”

Section: *mentioning

confidence: 99%

“…The data consists of minefields in beach sand with several varieties of obstacles and clutter objects (e.g., concrete barricades, hedgehogs, tetrahedrons). The processed mine detection results are in the form of images whose individual pixel values correspond to the COBRA mine detection algorithm strength (called "RX") for that particular pixel within the common area of a multispectral image (MSI) set [4,5,6,7]. A multispectral image set is comprised ofN separate images measured at different wavelengths, with N being the total number of spectral bands, or wavelengths.…”

Section: Statistical Data Collection/extractionmentioning

confidence: 99%

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COBRA ATD minefield detection model initial performance analysis

et al. 2000

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A statistical performance analysis of the USMC Coastal Battlefield Reconnaissance and Analysis (COBRA) Minefield Detection (MFD) Model has been performed in support of the COBRA ATD (Advanced Technology Demonstration) Program under execution by the Naval Surface Warfare Center/Dahigren Division/Coastal Systems Station (NSWC/DD/CSS). This analysis uses the Vendian ERIM International (V-ERIM) MFD model from the COBRA Sensor Performance Evaluation and Computational Tools for Research Analysis (SPECTRA) modeling toolbox and a collection of multispectral mine detection algorithm response distributions for mines and minelike clutter objects. These mine detection response distributions were generated from actual COBRA ATD test missions over littoral zone minefields. This analysis serves to validate both the utility and effectiveness of the COBRA MFD Model as a predictive MFD performance tool. COBRA ATh minefield detection model algorithm performance results based on a simulated baseline minefield detection scenario (minefield configuration, flight path, and sensor configuration) are presented, as well as results of a MFD model algorithm parametric sensitivity study.

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