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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Waxman, A. Fay, D. Ilardi, P. Arambel, P. Xinzhuo Shen Krant, J. Moore, T. Gorin, B. Tilden, S. Baron, B. Lobowiecki, J. Jelavic, R. Verbiar, C. Antoniades, J. Baumback, M. Hass, D. Edwards, J. Henderson, S. Chester, D. |
| Copyright Year | 2009 |
| Description | Author affiliation: BAE Systems, Greenlawn, NY; USA (Gorin, B.; Tilden, S.; Baron, B.; Lobowiecki, J.; Jelavic, R.; Verbiar, C.) || BAE Systems, Burlington, MA; USA (Waxman, A.; Fay, D.; Ilardi, P.; Arambel, P.; Xinzhuo Shen; Krant, J.; Moore, T.) || BAE Systems, Columbia, MD; USA (Antoniades, J.; Baumback, M.; Hass, D.; Edwards, J.; Henderson, S.; Chester, D.) |
| Abstract | At Fusion 2007 we presented real-time methods for fused video imaging, detection and tracking of multiple ground targets, and showed results of tower-based ground tests. This paper summarizes the use of these methods in proof of concept flight tests, undertaken as a collaborative effort among several business units of BAE Systems North America. Utilizing a Sonoma commercial RGB/MWIR 4-band turret mounted on a King Air 90, we integrated our existing image co/geo-registration methods with the image fusion, target learning & detection, multi-target tracking, and sensor/turret resource management methods reported previously, implemented them on real-time commercial processors, and conducted two test flights over water and land. We illustrate results of these flight tests that demonstrate proof of concept capabilities, showing examples of air-to-surface detection and tracking of multiple vessels over an extended field of regard, ground vehicles (both stationary and moving), and multiple dismounts walking on a beach. The approach does not require stabilization of the background in order to detect moving targets because detection is all spectral-based. Targets can be detected as spectral anomalies with respect to an adaptive local background, and then learned on-the-fly as a target class. Alternatively, targets can be designated by an operator and learned in real-time. This approach applies to both day & night fused video imaging over land & water, and can be extended to include other imaging sensors such as SWIR & LWIR, and coupled with hyperspectral fingerprinting for feature-aided tracking. |
| Starting Page | 1439 |
| Ending Page | 1443 |
| File Size | 3218293 |
| Page Count | 5 |
| File Format | |
| ISBN | 9780982443804 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-07-06 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | ISIF |
| Subject Keyword | Infrared detectors Target tracking Hyperspectral imaging Gas detectors Image sensors Sensor fusion Hyperspectral sensors Optical imaging System testing Collaboration sensor resource management Video tracking multi-target tracking image fusion target detection neural networks |
| Content Type | Text |
| Resource Type | Article |
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