Subspace approach to direction finding of rapidly moving sources with an uniform linear array

2008 ◽  
Author(s):  
B. Demissie ◽  
P. Willett
Keyword(s):  
Linear Array ◽  
Direction Finding ◽  
Uniform Linear Array ◽  
Moving Sources

scholarly journals SBL-Based Direction Finding Method with Imperfect Array

Electronics ◽  
2018 ◽  
Vol 7 (12) ◽  
pp. 426 ◽  
Author(s):  
Peng Chen  ◽  
Zhimin Chen ◽  
Xuan Zhang ◽  
Linxi Liu
Keyword(s):  
Mutual Coupling ◽  
Bayesian Learning ◽  
Linear Array ◽  
State Of The Art ◽  
Coupling Effect ◽  
Direction Finding ◽  
Noise Variance ◽  
Uniform Linear Array ◽  
Unknown Parameters ◽  
Finding Method

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.

scholarly journals How Varying the Dipole Lengths of a Uniform Linear Array Affects the Performance of an ESPRIT based Direction Finding Algorithm

2020 ◽  
Vol 14 ◽  
Keyword(s):  
Method Of Moments ◽  
Mutual Coupling ◽  
Linear Array ◽  
Direction Of Arrival ◽  
Direction Finding ◽  
Direction Of Arrival Estimation ◽  
Simulation Tool ◽  
Uniform Linear Array ◽  
Coupling Matrix ◽  
Esprit Algorithm

Popularly used to collect data for the direction-of-arrival estimation of an incident source. Since the dipole elements of the uniform linear array are electromagnetically and mutually coupled, the presence of mutual coupling may degrade the performance of any direction finding algorithms. In order to mitigate mutual coupling, several references introduced modifications of the well-known ESPRIT algorithm. These modifications involve discarding the data collected by linear array at the two ends. However, the assumption of several literature that the mutual coupling matrix to be both Toeplitz and banded are invalid. This is pointed out by the “method of moments” based computer simulation tool used in this paper. The Toeplitz-and-banded coupling-matrix assumption leads to the mutual coupling being mis-modeled. Furthermore, previous studies failed to consider how varying the dipoles’ electrical length affect the performance of the direction-of-arrival estimation under mutual coupling.

Comparison between DOA Estimation Subspace methods for incoherent and coherent signals

2015 ◽  
Vol 1 ◽  
pp. 18
Author(s):  
Ahmed Abdalla ◽  
Suhad Mohammed ◽  
Tang Bin ◽  
Jumma Mary Atieno ◽  
Abdelazeim Abdalla
Keyword(s):  
Linear Array ◽  
Doa Estimation ◽  
Far Field ◽  
Matlab Simulation ◽  
Subspace Methods ◽  
Coherent Signals ◽  
Uniform Linear Array ◽  
Pros And Cons ◽  
Basic Concepts ◽  
And Performance

This paper considers the problem of estimating the direction of arrival (DOA) for the both incoherent and coherent signals from narrowband sources, located in the far field in the case of uniform linear array sensors. Three different methods are analyzed. Specifically, these methods are Music, Root-Music and ESPRIT. The pros and cons of these methods are identified and compared in light of different viewpoints. The performance of the three methods is evaluated, analytically, when possible, and by Matlab simulation. This paper can be a roadmap for beginners in understanding the basic concepts of DOA estimation issues, properties and performance.

scholarly journals Micro Non-Uniform Linear Array (MNULA) for Ultrasound Plane Wave Imaging

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 640
Author(s):  
Yujia Tang ◽  
Zhangjian Li ◽  
Yaoyao Cui ◽  
Chen Yang ◽  
Jiabing Lv ◽  
...  
Keyword(s):  
Plane Wave ◽  
Linear Array ◽  
Near Field ◽  
Uniform Linear Array ◽  
Imaging Technology ◽  
Linear Arrays ◽  
Imaging Quality ◽  
Imaging Results ◽  
Wave Imaging ◽  
Laboratory Technology

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.

scholarly journals Compressed Sensing-Based DOA Estimation with Unknown Mutual Coupling Effect

Electronics ◽  
2018 ◽  
Vol 7 (12) ◽  
pp. 424 ◽  
Author(s):  
Peng Chen ◽  
Zhenxin Cao ◽  
Zhimin Chen ◽  
Linxi Liu ◽  
Man Feng
Keyword(s):  
Compressed Sensing ◽  
Mutual Coupling ◽  
Linear Array ◽  
State Of The Art ◽  
Coupling Effect ◽  
Estimation Method ◽  
Doa Estimation ◽  
System Model ◽  
Reconstruction Problem ◽  
Uniform Linear Array

The performance of a direction-finding system is significantly degraded by the imperfection of an array. In this paper, the direction-of-arrival (DOA) estimation problem is investigated in the uniform linear array (ULA) system with the unknown mutual coupling (MC) effect. The system model with MC effect is formulated. Then, by exploiting the signal sparsity in the spatial domain, a compressed-sensing (CS)-based system model is proposed with the MC coefficients, and the problem of DOA estimation is converted into that of a sparse reconstruction. To solve the reconstruction problem efficiently, a novel DOA estimation method, named sparse-based DOA estimation with unknown MC effect (SDMC), is proposed, where both the sparse signal and the MC coefficients are estimated iteratively. Simulation results show that the proposed method can achieve better performance of DOA estimation in the scenario with MC effect than the state-of-the-art methods, and improve the DOA estimation performance about 31.64 % by reducing the MC effect by about 4 dB.

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