An iterative dictionary learning-based algorithm for DOA estimation

Zamani, H ; Sharif University of Technology

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  1. Type of Document: Article
  2. DOI: 10.1109/LCOMM.2016.2587674
  3. Publisher: Institute of Electrical and Electronics Engineers Inc
  4. Abstract:
  5. This letter proposes a dictionary learning algorithm for solving the grid mismatch problem in direction of arrival (DOA) estimation from both the array sensor data and from the sign of the array sensor data. Discretization of the grid in the sparsity-based DOA estimation algorithms is a problem, which leads to a bias error. To compensate this bias error, a dictionary learning technique is suggested, which is based on minimizing a suitable cost function. We also propose an algorithm for the estimation of DOA from the sign of the measurements. It extends the iterative method with adaptive thresholding algorithm to the 1-b compressed sensing framework. Simulation results show the effectiveness of the dictionary learning-based algorithms in comparison with the counterpart algorithms in DOA estimation both from the sensors' data and from the sign of the sensors' data
  6. Keywords:
  7. Sign of the measurements ; Steepest-descent ; Compressed sensing ; Cost functions ; Iterative methods ; Learning algorithms ; Signal reconstruction ; Steepest descent method ; Adaptive thresholding ; Dictionary learning ; Dictionary learning algorithms ; Direction of arrivalestimation(DOA) ; Discretizations ; DOA estimation ; DOA estimation algorithms ; Mismatch problems ; Direction of arrival
  8. Source: IEEE Communications Letters ; Volume 20, Issue 9 , 2016 , Pages 1784-1787 ; 10897798 (ISSN)
  9. URL: http://ieeexplore.ieee.org/document/7505977