2-D Sparse Autoregressive Modeling For High Resolution Radar Imaging

OZEN B., Erer I.

24th Signal Processing and Communication Application Conference (SIU), Zonguldak, Turkey, 16 - 19 May 2016, pp.857-860 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/siu.2016.7495875
  • City: Zonguldak
  • Country: Turkey
  • Page Numbers: pp.857-860
  • Istanbul Technical University Affiliated: Yes


ISAR imaging based on autoregressive (AR) model has not only spurious scattering centers but also high side lobes. Sparse AR models can be utilized for suppressing these. However, computational complexity of the BPDN with penalty sparsity approach which is employed to compute sparse AR model coefficients is high. In this work, the sparse AR model coefficients are computed by using BPDN and LASSO approaches which have less computational complexity. Spurious scattering centers and side lobes are successfully suppressed in the resulting radar images.