Detection of Spatially Unresolved (Nominally Sub-Pixel) Submerged and Surface Targets Using Hyperspectral Data
Approved for public release; distribution is unlimited === Due to the United States dependency on maritime travel, the proliferation of efficient and inexpensive naval mines poses a tremendous risk. Current MCM technologies have narrow FOVs, preventing timely, wide-area searches. These technologies...
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Monterey, California. Naval Postgraduate School
2012
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ndltd-nps.edu-oai-calhoun.nps.edu-10945-173302015-08-06T16:03:02Z Detection of Spatially Unresolved (Nominally Sub-Pixel) Submerged and Surface Targets Using Hyperspectral Data Burt, Christopher B. Olsen, Richard C. Trask, David Remote Sensing Intelligence Approved for public release; distribution is unlimited Due to the United States dependency on maritime travel, the proliferation of efficient and inexpensive naval mines poses a tremendous risk. Current MCM technologies have narrow FOVs, preventing timely, wide-area searches. These technologies require the operator to be in proximity to the targets, a dangerous scenario made worse when in denied territory. In an effort to mitigate these risks, the use of a high altitude hyperspectral sensor is proposed. The operational ability of a hyperspectral sensor to detect sub-pixel surface and submerged mines in non-littoral environments was evaluated using visual inspection and two common anomaly detectors Mixture Tuned Matched Filtering (MTMF) and Reed-Xiaoli (RX). Due to the unavailability of the DoDs Spectral Infrared Imaging Technology Testbed (SPIRITT), ProSpecTIR-VS3, a sensor similar spatially and spectrally to SPIRITT was flown over a range offshore California. This experiment included three surface and three submerged targets, each with a 0.8 meter diameter. Both 0.5 and 1 meter spatial resolution data were collected, allowing for both a resolved and unresolved analysis. While both anomaly detection techniques have their flaws, the success of this study is in proving the usefulness of hyperspectral data for sub-pixel mine detection. 2012-11-14T00:02:16Z 2012-11-14T00:02:16Z 2012-09 Thesis http://hdl.handle.net/10945/17330 Monterey, California. Naval Postgraduate School |
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Approved for public release; distribution is unlimited === Due to the United States dependency on maritime travel, the proliferation of efficient and inexpensive naval mines poses a tremendous risk. Current MCM technologies have narrow FOVs, preventing timely, wide-area searches. These technologies require the operator to be in proximity to the targets, a dangerous scenario made worse when in denied territory. In an effort to mitigate these risks, the use of a high altitude hyperspectral sensor is proposed. The operational ability of a hyperspectral sensor to detect sub-pixel surface and submerged mines in non-littoral environments was evaluated using visual inspection and two common anomaly detectors Mixture Tuned Matched Filtering (MTMF) and Reed-Xiaoli (RX). Due to the unavailability of the DoDs Spectral Infrared Imaging Technology Testbed (SPIRITT), ProSpecTIR-VS3, a sensor similar spatially and spectrally to SPIRITT was flown over a range offshore California. This experiment included three surface and three submerged targets, each with a 0.8 meter diameter. Both 0.5 and 1 meter spatial resolution data were collected, allowing for both a resolved and unresolved analysis. While both anomaly detection techniques have their flaws, the success of this study is in proving the usefulness of hyperspectral data for sub-pixel mine detection. |
author2 |
Olsen, Richard C. |
author_facet |
Olsen, Richard C. Burt, Christopher B. |
author |
Burt, Christopher B. |
spellingShingle |
Burt, Christopher B. Detection of Spatially Unresolved (Nominally Sub-Pixel) Submerged and Surface Targets Using Hyperspectral Data |
author_sort |
Burt, Christopher B. |
title |
Detection of Spatially Unresolved (Nominally Sub-Pixel) Submerged and Surface Targets Using Hyperspectral Data |
title_short |
Detection of Spatially Unresolved (Nominally Sub-Pixel) Submerged and Surface Targets Using Hyperspectral Data |
title_full |
Detection of Spatially Unresolved (Nominally Sub-Pixel) Submerged and Surface Targets Using Hyperspectral Data |
title_fullStr |
Detection of Spatially Unresolved (Nominally Sub-Pixel) Submerged and Surface Targets Using Hyperspectral Data |
title_full_unstemmed |
Detection of Spatially Unresolved (Nominally Sub-Pixel) Submerged and Surface Targets Using Hyperspectral Data |
title_sort |
detection of spatially unresolved (nominally sub-pixel) submerged and surface targets using hyperspectral data |
publisher |
Monterey, California. Naval Postgraduate School |
publishDate |
2012 |
url |
http://hdl.handle.net/10945/17330 |
work_keys_str_mv |
AT burtchristopherb detectionofspatiallyunresolvednominallysubpixelsubmergedandsurfacetargetsusinghyperspectraldata |
_version_ |
1716816304057352192 |