DocumentCode :
2289599
Title :
Artificial intelligence and waveform diversity
Author :
Capraro, Gerard T. ; Capraro, C.T. ; Wicks, Michael C. ; Liuzzi, Raymond A.
Author_Institution :
Capraro Technol., Utica, NY, USA
fYear :
2003
fDate :
30 Sept.-4 Oct. 2003
Firstpage :
270
Lastpage :
274
Abstract :
Future US Air Force sensor systems must be able to adapt to changing environments in real time. A capabilities-based modeling approach offers a new method for building the next generation weapon system. To accommodate this model based approach, the Department of Defense (DoD) is promoting the use of waveform diversity for active radar systems. Building a weapon system including one or more systems with waveform diversity will require the use of artificial intelligence (AI) tools and techniques. We provide a model of how an aircraft sensor system can be retrofitted to accommodate radars employing waveform diversity without causing fratricide.
Keywords :
airborne radar; artificial intelligence; intelligent sensors; space-time adaptive processing; AI; active radar system; aircraft sensor system; artificial intelligence techniques; capabilities-based modeling approach; waveform diversity; Aircraft; Artificial intelligence; Force sensors; Intelligent sensors; Laboratories; Radar; Real time systems; Sensor systems; Signal processing algorithms; Weapons;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Integration of Knowledge Intensive Multi-Agent Systems, 2003. International Conference on
Print_ISBN :
0-7803-7958-6
Type :
conf
DOI :
10.1109/KIMAS.2003.1245056
Filename :
1245056
Link To Document :
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