• DocumentCode
    1680569
  • Title

    Parameters estimation of LFM signal based on fusion of signals with the same length and known frequency-difference

  • Author

    Xiao, Wei ; Tu, Y.-Q. ; Liu, L.-B. ; Mao, Y.-W. ; Xu, Hua

  • Author_Institution
    Dept. of Inf. Eng., Logistical Eng. Univ., Chongqing, China
  • fYear
    2010
  • Firstpage
    6776
  • Lastpage
    6781
  • Abstract
    To attain fast and accurate parameters estimation of LFM signal under low signal and noise ratio conditions, a novel algorithm is presented. In this algorithm, LFM signal is first converted into multi-section signals with the same length and known frequency-difference by an easy sampling method, and the relation between the parameters of LFM signal and frequencies as well as frequency-differences of these multi-section signals is deduced. Then these multi-section signals are fused into one fusion signal by some techniques such as parameter matrix frequency-domain analysis,phase-difference compensating factor matrix and search frequency array. At last, high precision parameters estimation of LFM signal are gotten by frequencies estimation of the fusion signal through an algorithm based on fusing multi-section signals with the same length and known frequency- difference. The results show that the presented algorithm is with good noise immunity, good universality, high precision of parameter estimation, as well as nicer performance under low signal and noise ratio conditions.
  • Keywords
    frequency estimation; frequency-domain analysis; matrix algebra; signal sampling; LFM signal; frequency estimation; fusion signal; linear frequency modulated signal; parameter matrix frequency-domain analysis; parameters estimation; phase-difference compensating factor matrix; sampling method; search frequency array; Algorithm design and analysis; Frequency conversion; Frequency estimation; Frequency modulation; Signal to noise ratio; LFM signal; frequency estimation; fusion signals with the same length and known frequency-difference; low signal and noise ratio(SNR); parameters estimation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Automation (WCICA), 2010 8th World Congress on
  • Conference_Location
    Jinan
  • Print_ISBN
    978-1-4244-6712-9
  • Type

    conf

  • DOI
    10.1109/WCICA.2010.5554180
  • Filename
    5554180