A New Algorithm of Range and DOA Estimation of Near Field Sources Based on FLOS-ESPRIT

2014 ◽  
Vol 577 ◽  
pp. 745-748
Author(s):  
Li Guo Wang
Keyword(s):  
Order Statistics ◽  
Computer Simulations ◽  
Lower Order ◽  
Linear Array ◽  
Near Field ◽  
Doa Estimation ◽  
Estimation Accuracy ◽  
Uniform Linear Array ◽  
Joint Estimate ◽  
Fractional Lower Order Statistics

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.

scholarly journals Off-Grid DoA Estimation on Non-Uniform Linear Array Using Constrained Hermitian Matrix

Energies ◽  
2020 ◽  
Vol 13 (21) ◽  
pp. 5775
Author(s):  
Hyeonjin Chung ◽  
Jeungmin Joo ◽  
Sunwoo Kim
Keyword(s):  
Toeplitz Matrix ◽  
Linear Array ◽  
Hermitian Matrix ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Estimation Accuracy ◽  
Uniform Linear Array ◽  
Atomic Norm ◽  
Array Structures ◽  
Simulation Results

In this paper, an off-grid direction-of-arrival (DoA) estimation algorithm which can work on a non-uniform linear array (NULA) is proposed. The original semidefinite programming (SDP) representation of the atomic norm exploits a summation of one-rank matrices constructed by atoms, where the summation of one-rank matrices equals a Hermitian Toeplitz matrix when using the uniform linear array (ULA). On the other hand, when the antennas in the array are placed arbitrarily, the summation of one-rank matrices is a Hermitian matrix whose diagonal elements are equivalent. Motivated by this property, the proposed algorithm replaces the Hermitian Toeplitz matrix in the original SDP with the constrained Hermitian matrix. Additionally, when the antennas are placed symmetrically, the performance can be enforced by adding extra constraints to the Hermitian matrix. The simulation results show that the proposed algorithm achieves higher estimation accuracy and resolution than other algorithms on both array structures; i.e., the arbitrary array and the symmetric 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.

Sensor Array Self-Calibration for Two-Dimensional Direction of Arrival Estimation

2012 ◽  
Vol 490-495 ◽  
pp. 534-537
Author(s):  
Da Wei Xiao ◽  
Jin Fang Cheng ◽  
Yi Liu
Keyword(s):  
Sensor Array ◽  
Linear Array ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Calibration Method ◽  
Estimation Accuracy ◽  
Two Dimensional ◽  
Uniform Linear Array ◽  
Actual Measurement ◽  
Self Calibration

In recent years, high-resolution Direction of Arrival (DOA) estimation with a sensor array has become indispensable for various applications. In actual measurement, however, DOA estimation accuracy is deteriorated by many error factors. For a uniform linear array (ULA), there exist algorithms for self-calibration for single-dimensional (1-D) DOA estimation. In this paper, we develop a simple self-calibration method for two-dimensional (2-D) DOA estimation with an L-shaped array.

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.

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