A covariance approximation method for near-field direction-finding using a uniform linear array

1995 ◽  
Vol 43 (5) ◽  
pp. 1293-1298 ◽  
Author(s):  
Ju-Hong Lee ◽  
Yih-Min Chen ◽  
Chien-Chung Yeh
Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 640
Author(s):  
Yujia Tang ◽  
Zhangjian Li ◽  
Yaoyao Cui ◽  
Chen Yang ◽  
Jiabing Lv ◽  
...  

Ultrasound plane wave imaging technology has been applied to more clinical situations than ever before because of its rapid imaging speed and stable imaging quality. Most transducers used in plane wave imaging are linear arrays, but their structures limit the application of plane wave imaging technology in some special clinical situations, especially in the endoscopic environment. In the endoscopic environment, the size of the linear array transducer is strictly miniaturized, and the imaging range is also limited to the near field. Meanwhile, the near field of a micro linear array has serious mutual interferences between elements, which is against the imaging quality of near field. Therefore, we propose a new structure of a micro ultrasound linear array for plane wave imaging. In this paper, a theoretical comparison is given through sound field and imaging simulations. On the basis of primary work and laboratory technology, micro uniform and non-uniform linear arrays were made and experimented with the phantom setting. We selected appropriate evaluation parameters to verify the imaging results. Finally, we concluded that the micro non-uniform linear array eliminated the artifacts better than the micro uniform linear array without the additional use of signal processing methods, especially for target points in the near-field. We believe this study provides a possible solution for plane wave imaging in cramped environments like endoscopy.


Electronics ◽  
2018 ◽  
Vol 7 (12) ◽  
pp. 426 ◽  
Author(s):  
Peng Chen  ◽  
Zhimin Chen ◽  
Xuan Zhang ◽  
Linxi Liu

The imperfect array degrades the direction finding performance. In this paper, we investigate the direction finding problem in uniform linear array (ULA) system with unknown mutual coupling effect between antennas. By exploiting the target sparsity in the spatial domain, the sparse Bayesian learning (SBL)-based model is proposed and converts the direction finding problem into a sparse reconstruction problem. In the sparse-based model, the off-grid errors are introduced by discretizing the direction area into grids. Therefore, an off-grid SBL model with mutual coupling vector is proposed to overcome both the mutual coupling and the off-grid effect. With the distribution assumptions of unknown parameters including the noise variance, the off-grid vector, the received signals and the mutual coupling vector, a novel direction finding method based on SBL with unknown mutual coupling effect named DFSMC is proposed, where an expectation-maximum (EM)-based step is adopted by deriving the estimation expressions for all the unknown parameters theoretically. Simulation results show that the proposed DFSMC method can outperform state-of-the-art direction finding methods significantly in the array system with unknown mutual coupling effect.


2020 ◽  
Vol 106 ◽  
pp. 102824
Author(s):  
Hongqing Liu ◽  
Huan Meng ◽  
Lu Gan ◽  
Dong Li ◽  
Yi Zhou ◽  
...  

Author(s):  
Sanjay Manjunath ◽  
A Anil Kumar ◽  
M Girish Chandra ◽  
Tapas Chakravarty

2014 ◽  
Vol 577 ◽  
pp. 745-748
Author(s):  
Li Guo Wang

A new algorithm based on fractional lower order statistics (FLOS) is presented to joint estimate the range and direction of arrival (DOA) parameters of near-field sources. The proposed algorithm adopts centra-symmetric uniform linear array, and constructs three fractional lower order statistics matrixes by the received array data, and utilizes TLS method to estimate the two dimension parameters, the algorithm has high estimation accuracy, only need a parameters pairing easily. The performance of proposed method is verified by computer simulations.


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