Precession missile feature extraction using sparse component analysis of radar measurements

نویسندگان

  • Lihua Liu
  • Xiaoyong Du
  • Mounir Ghogho
  • Weidong Hu
  • Desmond C. McLernon
چکیده

According to the working mode of the ballistic missile warning radar (BMWR), the radar return from the BMWR is usually sparse. To recognize and identify the warhead, it is necessary to extract the precession frequency and the locations of the scattering centers of the missile. This article first analyzes the radar signal model of the precessing conical missile during flight and develops the sparse dictionary which is parameterized by the unknown precession frequency. Based on the sparse dictionary, the sparse signal model is then established. A nonlinear least square estimation is first applied to roughly extract the precession frequency in the sparse dictionary. Based on the time segmented radar signal, a sparse component analysis method using the orthogonal matching pursuit algorithm is then proposed to jointly estimate the precession frequency and the scattering centers of the missile. Simulation results illustrate the validity of the proposed method.

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عنوان ژورنال:
  • EURASIP J. Adv. Sig. Proc.

دوره 2012  شماره 

صفحات  -

تاریخ انتشار 2012