الفهرس 
INTRODUCTIONOnly 14 pages are availabe for public view
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Abstract
Most recent state-of-the-art narrowband and wideband Direction of Arrival (DOA) estimation techniques achieve reasonable accuracy at the expense of high computational complexity. In this thesis, a new computationally efficient approach based on Compressive Sensing (CS) is introduced for high resolution narrowband and wideband DOA estimation. The low system complexity is achieved using CS with deterministic chaotic Chebyshev sensing matrices that allow reducing the measurement vector dimension, while the high-resolution DOA estimation is acquired utilizing an efficient generalized coprime array configuration. The efficiency of the proposed approach in enhancing the DOA estimation accuracy and reducing the computational complexity is studied along with a simultaneously held comparison between two state-of-the-art narrowband DOA estimation techniques, namely, Capon and Multiple Signal Classification (MUSIC), and three wideband DOA estimation techniques, namely, Incoherent Signal Subspace Method (ISSM), Focusing Signal Subspace (FSS) and modified Test of Orthogonality of Projected Subspaces (mTOPS) with and without applying the proposed CS technique. The effectiveness of employing the introduced generalized coprime antenna array configuration is demonstrated by comparing its performance with the Uniform linear antenna array (ULA) configuration for all cases under investigation. The performance is examined utilizing various assessment metrics such as the spatial spectrum, the computational time, and the Root Mean Square Error (RMSE) between estimated and actual DOAs when varying the Signal to Noise Ratio (SNR) and number of elements. Results reveal that applying the proposed CS technique to the two narrowband algorithms (Capon and MUSIC) and the three algorithms (ISSM, FSS, and mTOPS) provides significant reduction in the execution time needed for the DOA estimation process without affecting the resolution accuracy under various set of parameters. This demonstrates the effectiveness of the proposed DOA estimation approach in real-time wireless systems.