• 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