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Beamforming and DOA Estimation Using Compressive Sensing and Random Sampling

Zamani, Hojatollah | 2015

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 48027 (05)
  4. University: Sharif University of Technology
  5. Department: Electrical Engineering
  6. Advisor(s): Marvasti, Farrokh
  7. Abstract:
  8. Direction Of Arrival (DOA) estimation or direction finding refers to determining the arrival angle of a planar wave impinging on the array of sensors or antennas. The DOA information can be used by the smart antenna system for beam-forming and reliable data transmission. The problem of DOA estimation in propagating plane waves played a fundamental role in many applications including acoustic, wireless communication systems, navigation, biomedical imaging, radar/sonar systems, seismic sensing, and wireless 911 emergency call locating. In the conventional DOA estimating systems, an array of elements (antennas or sensors) is used that are colocated in a uniform pattern called, Uniform Linear Array (ULA). In order to achieve an acceptable estimation accuracy in such systems, the number of array elements should be more than that of the sources propagating the waves. However, the computational complexity of the receiver is increased with increasing the number of array elements. Hence, designing a DOA estimation scheme which requires fewer number of array elements in the receiver side is of paramount importance.Compressive sensing technique used for efficiently acquiring and reconstructing a signal by solving an under-determined linear problems. Some reconstruction methods such as BP, BPDN, LASSO which using convex optimization for solving l1 minimization problem. Using convex optimization make high complexity which can not operate on real systems such as DOA estimation. Some greedy algorithms such as OMP is faster in time complexity than mentioned methods with the performance degradation. In this thesis we reconstruct the data elements of array by using random sampling and IMAT(Iterative Method with Adaptive Thresholding) method and also solving under-determined linear problems with IMATCS. In this thesis, we propose a new structure, random array, in order to estimate the Direction Of Arrival (DOA). The proposed DOA estimation scheme exploits the random sampling concept to reduce the number of array elements required for a reliable DOA estimation task. Combining the ideas of random sampling and compressed sensing recovery, we introduce an efficient technique called Iterative Method with Adaptive Thresholding using Interpolation and Compressed Sensing (IMATICS), for estimating the direction of arrival directly from a random pattern of the array elements. As the array elements can have any arbitrary random pattern, the DOA estimation scheme is considerably robust against any array element outages or misplacements
  9. Keywords:
  10. Direction of Arrival (DOA)Estimation ; Beam Shaping ; Compressive Sensing ; Random Sampling ; Sparse Recovery ; Iteration Method ; Array Signal Processing

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