Compressive sensing-based coprime array direction-of-arrival estimation

2017 ◽  
Vol 11 (11) ◽  
pp. 1719-1724 ◽  
Author(s):  
Chengwei Zhou ◽  
Yujie Gu ◽  
Yimin D. Zhang ◽  
Zhiguo Shi ◽  
Tao Jin ◽  
...  
2021 ◽  
Author(s):  
Jingjing Cai ◽  
Xueyan Chang ◽  
Wei Liu ◽  
Tao Shang ◽  
Chao Li

Author(s):  
Mohammed A. Yafeai ◽  
Abdulmalik H. Almazrua ◽  
Saleh A. Alawsh ◽  
Ahmad I. Oweis ◽  
Ali H. Muqaibel ◽  
...  

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Hamid Ali Mirza ◽  
Laeeq Aslam ◽  
Muhammad Asif Zahoor Raja ◽  
Naveed Ishtiaq Chaudhary ◽  
Ijaz Mansoor Qureshi ◽  
...  

In this paper, a method for solving grid mismatch or off-grid target is presented for direction of arrival (DOA) estimation problem using compressive sensing (CS) technique. Location of the sources are at few angles as compare to the entire angle domain, i.e., spatially sparse sources, and their location can be estimated using CS methods with ability of achieving super resolution and estimation with a smaller number of samples. Due to grid mismatch in CS techniques, the source energy is distributed among the adjacent grids. Therefore, a fitness function is introduced which is based on the difference of the source energy among the adjacent grids. This function provides the best discretization value for the grid through iterative grid refinement. The effectiveness of the proposed scheme is verified through extensive simulations for different number of sources.


2021 ◽  
Vol 4 (2) ◽  
pp. 23-32
Author(s):  
Fatimah A. Salman ◽  
Bayan M. Sabbar

Sparse array such as the coprime array is one of the most preferable sparse arrays for direction of arrival estimation due to its properties, like simplicity, capability of resolving more sources than the number of elements and resistance to mutual coupling issue.  In this paper, a new coprime array model is proposed to increase the number of degree of freedom (DOF) and improve the performance of coprime array.   The new designed array can avoid the mutual coupling by minimizing the lag redundancy and expand the central lags in the virtual difference co-array. Thus, the propose structure can resolve more sources than the prototype coprime array using the same number of elements with improved direction of arrival estimation. Simulation results demonstrate that the proposed array model is more efficient than the others coprime array model.


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