Erratum for ‘Decoupled parameter estimation of multiple distributed sources for uniform linear array with low complexity’

2008 ◽  
Vol 44 (13) ◽  
pp. 832
Author(s):  
E.H. Bae ◽  
J.S. Kim ◽  
B.W. Choi ◽  
K.K. Lee
Keyword(s):  
Parameter Estimation ◽  
Linear Array ◽  
Low Complexity ◽  
Uniform Linear Array

Decoupled parameter estimation of multiple distributed sources for uniform linear array with low complexity

2008 ◽  
Vol 44 (10) ◽  
pp. 649 ◽  
Author(s):  
E.H. Bae ◽  
J.S. Kim ◽  
B.W. Choi ◽  
K.K. Lee
Keyword(s):  
Parameter Estimation ◽  
Linear Array ◽  
Low Complexity ◽  
Uniform Linear Array

scholarly journals PARALIND-based identifiability results for parameter estimation via uniform linear array

2012 ◽  
Vol 2012 (1) ◽  
Author(s):  
Xu Liu ◽  
Ting Jiang ◽  
Longxiang Yang ◽  
Hongbo Zhu
Keyword(s):  
Parameter Estimation ◽  
Linear Array ◽  
Uniform Linear Array

Second-Order Statistics-Based Multi-Parameter Estimation of Near-Field Acoustic Sources

2013 ◽  
Vol 461 ◽  
pp. 977-983
Author(s):  
Xin Bo Li ◽  
Nan Nan Liu ◽  
Nan Jiang ◽  
Xiao Bo Long ◽  
Xiao Yang Jiao
Keyword(s):  
Parameter Estimation ◽  
Order Statistics ◽  
Linear Array ◽  
Near Field ◽  
Second Order ◽  
Uniform Linear Array ◽  
Acoustic Vector Sensor ◽  
Second Order Statistics ◽  
Vector Sensor ◽  
Acoustic Sources

In this paper, a new approach based on the second-order statistics (SOS) and acoustic vector sensor (AVS) array is proposed, for localization estimation of near-field acoustic narrowband sources. Firstly, we choose the centrosymmetric uniform linear-array as the AVS arrangement, and the array is consistent with the coordinate axis direction of the acoustic vector-sensor. This estimation method makes good use of the acquisition information from the AVS, such as one-dimensional sound pressure and three-dimensional particle velocity, and has shown preferable performance for the parameter estimation of direction-of-arrival (DOA) and range of target acoustic sources in the near field. The estimation algorithm expands the near-field array manifold of one single acoustic vector sensor to the acoustic vector-sensor’s uniform linear-array, and the near-field acoustic vector sensor linear array output model is deduced. The autocorrelation and cross-correlation function of the velocity field and the pressure field are used to construct the rotational invariance frame, which helps to extract the expected information. Consequently, the closed-form solutions of the incident source’s DOA and range are derived explicitly through the parameter pairing operation. The proposed method reduces the computational burden and has good spatial recognition ability and high resolution in the case of limited array elements. It also has better engineering application prospect. Eventually, the performance of the method is verified by Monte Carlo simulation experiments.

scholarly journals A Low Complexity Subspace-Based DOA Estimation Algorithm with Uniform Linear Array Correlation Matrix Subsampling

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Do-Sik Yoo
Keyword(s):  
Linear Array ◽  
Signal To Noise Ratio ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Low Complexity ◽  
Eigenvalue Decomposition ◽  
Complex Eigenvalue ◽  
Uniform Linear Array ◽  
Autocorrelation Matrix ◽  
Value Decomposition

We propose a low complexity subspace-based direction-of-arrival (DOA) estimation algorithm employing a direct signal space construction method (DSPCM) by subsampling the autocorrelation matrix of a uniform linear array (ULA). Three major contributions of this paper are as follows. First of all, we introduce the method of autocorrelation matrix subsampling which enables us to employ a low complexity algorithm based on a ULA without computationally complex eigenvalue decomposition or singular-value decomposition. Secondly, we introduce a signal vector separation method to improve the distinguishability among signal vectors, which can greatly improve the performance, particularly, in low signal-to-noise ratio (SNR) regime. Thirdly, we provide a root finding (RF) method in addition to a spectral search (SS) method as the angle finding scheme. Through simulations, we illustrate that the performance of the proposed scheme is reasonably close to computationally much more expensive MUSIC- (MUltiple SIgnal Classification-) based algorithms. Finally, we illustrate that the computational complexity of the proposed scheme is reduced, in comparison with those of MUSIC-based schemes, by a factor ofO(N2/K), whereKis the number of sources andNis the number of antenna elements.

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 A Deflation Approach to Direction of Arrival Estimation for Symmetric Uniform Linear Array

2006 ◽  
Vol 5 ◽  
pp. 486-489 ◽  
Author(s):  
X. Xu ◽  
Z. Ye ◽  
Y. Zhang ◽  
C. Chang
Keyword(s):  
Linear Array ◽  
Direction Of Arrival ◽  
Direction Of Arrival Estimation ◽  
Uniform Linear Array
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