• DocumentCode
    2862844
  • Title

    Frequency-DOA joint estimation by Ant Colony Optimization

  • Author

    Jin, Yong ; Hou, Yunshan ; Jiang, Min

  • Author_Institution
    Inst. of Image Process. & Pattern Recognition, Henan Univ., Kaifeng, China
  • Volume
    15
  • fYear
    2010
  • fDate
    22-24 Oct. 2010
  • Abstract
    The Multiple Signal Classification (MUSIC) method is a typical method for high-resolution Direction Of Arrival(DOA) and frequency estimation. Usually it performs spectrum search in certain grid space, which inevitably leads to high computational cost in the multi-dimensional case, for example the search for frequency and azimuth at the same time. To overcome this problem, in this paper, we introduced Ant Colony Optimization(ACO) to work with MUSIC. A new kind of ACO for continuous domain featured by Gauss kernel function is used to sample the MUSIC spectrum, which is regarded as the fitness function in the process. The resulted estimator is called Ant Colony Optimization based MUSIC (ACO-MUSIC). Simulations show that ACO-MUSIC not only reduces the computational complexity greatly but also maintains the excellent performance of the original MUSIC estimator.
  • Keywords
    computational complexity; direction-of-arrival estimation; frequency estimation; optimisation; signal classification; Gauss kernel function; MUSIC method; ant colony optimization; computational complexity; direction of arrival estimation; frequency estimation; frequency-DOA joint estimation; grid space; multidimensional case; multiple signal classification; Multiple signal classification; Signal to noise ratio; ant colony optimization; computational complexity; direction of arrival; multiple signal classification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Application and System Modeling (ICCASM), 2010 International Conference on
  • Conference_Location
    Taiyuan
  • Print_ISBN
    978-1-4244-7235-2
  • Electronic_ISBN
    978-1-4244-7237-6
  • Type

    conf

  • DOI
    10.1109/ICCASM.2010.5622542
  • Filename
    5622542