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Compressive sensing for elliptic localization in MIMO radars

Zamani, H ; Sharif University of Technology

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  1. Type of Document: Article
  2. DOI: 10.1109/IranianCEE.2016.7585578
  3. Publisher: Institute of Electrical and Electronics Engineers Inc
  4. Abstract:
  5. In this paper, a sparsity-aware target localization method in multiple-input-multiple-output (MIMO) radars by utilizing time difference of arrival (TDOA) measurements is proposed. This method provides a maximum likelihood (ML) estimator for target position by employing compressive sensing techniques. Also, for fast convergence and mitigating the mismatch problem due to grid discretization, we address a block-based search coupled with an adaptive dictionary learning technique. The Cramer-Rao lower bound for this model is derived as a benchmark. Simulations results are included to verify the localization performance
  6. Keywords:
  7. Compressed sensing (CS) ; Dictionary learning (DL) ; Time difference of arrival (TDOA) ; Channel estimation ; Codes (symbols) ; Cramer-Rao bounds ; Direction of arrival ; Feedback control ; Maximum likelihood ; Maximum likelihood estimation ; MIMO systems ; Radar ; Radar measurement ; Signal reconstruction ; Telecommunication repeaters ; Tracking (position) ; Bistatic range ; Multiple input multiple output (MIMO) radars ; Target localization ; MIMO radar
  8. Source: 24th Iranian Conference on Electrical Engineering, 10 May 2016 through 12 May 2016 ; 2016 , Pages 525-528 ; 9781467387897 (ISBN)
  9. URL: http://ieeexplore.ieee.org/document/7585578