DocumentCode :
1931914
Title :
Using genetic algorithms for radar waveform selection
Author :
Capraro, Christopher T. ; Bradaric, Ivan ; Capraro, Gerard T. ; Lue, Tsu Kong
Author_Institution :
Capraro Technol., Inc., Utica, NY
fYear :
2008
fDate :
26-30 May 2008
Firstpage :
1
Lastpage :
6
Abstract :
Genetic algorithms have proven to be useful tools in optimizing complex problems with large solution spaces. Radar waveform selection is a challenging problem that may benefit from the use of genetic algorithms. Furthermore, advances in the areas of waveform diversity, multistatic radars and knowledge-aided radars are making waveform selection even more challenging. As a design tool we used genetic algorithms to perform waveform selection utilizing the autocorrelation and ambiguity functions in the fitness evaluation. Monostatic, bistatic and multistatic notional examples are presented and early results indicate that genetic algorithms can provide a useful and effective tool in waveform selection for a variety of radar configurations.
Keywords :
genetic algorithms; radar signal processing; waveform analysis; genetic algorithms; knowledge-aided radars; multistatic radars; radar waveform selection; waveform diversity; Algorithm design and analysis; Biological cells; Frequency; Genetic algorithms; Performance evaluation; Phased arrays; Radar antennas; Space technology; Space vector pulse width modulation; USA Councils; Genetic Algorithms; Multistatic Radar; Waveform Diversity; Waveform Selection;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Radar Conference, 2008. RADAR '08. IEEE
Conference_Location :
Rome
ISSN :
1097-5659
Print_ISBN :
978-1-4244-1538-0
Electronic_ISBN :
1097-5659
Type :
conf
DOI :
10.1109/RADAR.2008.4720947
Filename :
4720947
Link To Document :
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