• DocumentCode
    1790864
  • Title

    Statistical spatial resolution limit for ultrawideband MIMO noise radar

  • Author

    Xiaoli Zhou ; Hongqiang Wang ; Yongqiang Cheng ; Yuliang Qin

  • Author_Institution
    Sch. of Electron. Sci. & Eng., Nat. Univ. of Defense Technol., Changsha, China
  • fYear
    2014
  • fDate
    June 29 2014-July 2 2014
  • Firstpage
    440
  • Lastpage
    443
  • Abstract
    In this paper, the spatial resolution limit for ultrawideband (UWB) MIMO noise radar is presented based on the statistical resolution theory. The signal model of UWB MIMO noise radar is established, and the resolution of two closely spaced targets is modeled as a binary hypothesis test. The statistical spatial resolution limit (SSRL) for UWB MIMO noise radar is derived based on the generalized likelihood ratio test (GLRT) with the constraints on the probabilities of false alarm and detection. The effects of detection parameters, transmit waveforms, array geometry, signal-to-noise ratio (SNR) and parameters of target on the SSRL are analyzed. Compared with the conventional resolution defined by ambiguity function, the SSRL reflects the practical resolution ability of radar and can provide an optimization criterion for radar system design.
  • Keywords
    MIMO radar; radar detection; radar resolution; statistical analysis; ultra wideband radar; GLRT; SNR; SSRL; UWB MIMO noise radar; ambiguity function; array geometry; binary hypothesis test; closely-spaced target resolution; detection parameters; detection probability; false alarm probability; generalized likelihood ratio test; optimization criterion; practical resolution ability; radar system design; signal-to-noise ratio; statistical resolution theory; statistical spatial resolution limit; transmit waveforms; ultrawideband MIMO noise radar; MIMO; Manganese; Noise; Signal resolution; Spatial resolution; Ultra wideband radar; UWB MIMO noise radar; generalized likelihood ratio test; hypothesis test; statistical spatial resolution limit;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Statistical Signal Processing (SSP), 2014 IEEE Workshop on
  • Conference_Location
    Gold Coast, VIC
  • Type

    conf

  • DOI
    10.1109/SSP.2014.6884670
  • Filename
    6884670