Enhanced intelligence through optimized TCPED concepts for airborne ISR

Spitzer, Michael; Kappes, E.; Böker, D.

doi:10.1117/12.920606

Cited by 5 publications

(1 citation statement)

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“…Spitzer, Kappes, and Boker [16] recognized this need for interoperability, automatic dissemination, and exploitation of data derived from systems deployed in the operational theatres. Their proposed model for tasking, collecting, processing, exploiting, and disseminating data provides insight into the effective fusion of data obtained from intelligence, surveillance, and reconnaissance (ISR) missions and networked assets.…”

Section: Scope and Limitationsmentioning

confidence: 99%

Multi-Sensor Image Fusion for Target Recognition in the Environment of Network Decision Support Systems

Pothitos¹

2015

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Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instruction, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the 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 Washington This thesis proposed a concept of distributed management of littoral operations at the tactical level, in which timeliness of information and reduced decision cycles are of critical importance. The use of mesh tactical networks augmented by sensor management, operational databases, and an appropriate level of automation of target recognition can turn the obstacles of land masses in littoral environments into a tactical advantage. Ultimately, this thesis concept aimed to enhance situational awareness by enabling the timely exploitation and dissemination of imagery data from small satellites and unmanned systems at the tactical level.Analyses of simulation and field experimentation results that focused on mobile ad-hoc networks (MANETs)-which connected dissimilar imaging sensors and enabled fusion of captured imagessupported this concept. Mesh tactical radios provided an adequate range and quality of service (QoS) to enable networking of kinetic and non-kinetic assets equipped with imaging or data relaying capabilities and to support dissemination of imagery data. Additionally, multi-spectral image fusion of thermal and visual images for target recognition yielded the best classification performance after the use of speeded-up robust features (SURF) and artificial neural networks (ANNs). SUBJECT TERMS MULTI-SENSOR IMAGE FUSION FOR TARGET RECOGNITION IN THE ENVIRONMENT OF NETWORK DECISION SUPPORT SYSTEMSMichail Pothitos Lieutenant Commander, Hellenic Navy B.S., Hellenic Naval Academy, 1999Submitted in partial fulfillment of the requirements for the degrees of MASTER OF SCIENCE IN COMBAT SYSTEMS TECHNOLOGYand MASTER OF SCIENCE IN SYSTEMS TECHNOLOGY (COMMAND, CONTROL & COMMUNICATIONS)from the NAVAL POSTGRADUATE SCHOOL December 2015Approved

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Section: Scope and Limitationsmentioning

confidence: 99%