scholarly journals A Two-Dimensional DOA Estimation Method Based on Virtual Extension of Sparse Array

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Guibao Wang ◽  
Peiyao Zhao ◽  
Lanmei Wang ◽  
Xiangyu Wang ◽  
Huan Wang ◽  
...  
Keyword(s):  
Absolute Convergence ◽  
Estimation Method ◽  
Operator Method ◽  
Doa Estimation ◽  
Fixed Number ◽  
Half Wavelength ◽  
Noncircular Signal ◽  
Array Aperture ◽  
Selection Operator ◽  
Coprime Array

The interelement spacing of a coprime array breaks through the half-wavelength limitation, so that a larger array aperture can be obtained with a fixed number of array elements. In this paper, the symmetry of the noncircular signal is used to virtually expand the L-shaped array into an orthogonal cross array. Furthermore, the virtual received signal of the augmented array is obtained by the second-order statistic of the received data. Decoupling and dimension reduction of elevation and azimuth are realized by a z-axis subarray and y-axis subarray. Finally, the sparse reconstruction of the signal is realized by the minimum absolute convergence and selection operator method. This method can enlarge the aperture and freedom of array and has higher accuracy and resolution of DOA estimation. It has the advantages of automatic parameter pairing without additional pairing operation and is effective for coherent and incoherent signals. The final numerical simulation results prove the effectiveness of the method in this paper.

scholarly journals 2-D DOA estimation method based on coprime array MIMO radar

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Fei Zhang ◽  
Zijing Zhang ◽  
Aisuo Jin ◽  
Chuantang Ji ◽  
Yi Wang
Keyword(s):  
Degrees Of Freedom ◽  
Estimation Method ◽  
Doa Estimation ◽  
Mimo Radar ◽  
Estimation Methods ◽  
Estimation Accuracy ◽  
Multiple Sources ◽  
Source Estimation ◽  
Array Aperture ◽  
Coprime Array

AbstractAiming at the problem that traditional direction of arrival (DOA) estimation methods cannot handle multiple sources with high accuracy while increasing the degrees of freedom (DOF), a new method for 2-D DOA estimation based on coprime array MIMO radar (SA-MIMO-CA) is proposed. First of all, in order to ensure the accuracy of multi-source estimation when the number of elements is finite, a new coprime array model based on MIMO (MIMO-CA) is proposed. This method is based on a new MIMO array-based co-prime array model (MIMO-CA), which improves the accuracy of multi-source estimation when the number of array elements is limited, and obtains a larger array aperture with a smaller number of array elements, and improves the estimation accuracy of 2-D DOA. Finally, the effectiveness and reliability of the proposed SM-MIMO-CA method in improving the DOF of array and DOA accuracy are verified by experiments.

scholarly journals Direction-of-Arrival Estimation of Closely Spaced Emitters Using Compact Arrays

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Hoi-Shun Lui ◽  
Hon Tat Hui
Keyword(s):  
Performance Evaluation ◽  
Matrix Pencil ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Antenna Element ◽  
Portable Devices ◽  
Estimation Algorithms ◽  
Half Wavelength ◽  
Matrix Pencil Method ◽  
Array Aperture

Performance evaluation of direction-of-arrival (DOA) estimation algorithms has continuously drawn significant attention in the past years. Most previous studies were conducted under the situation that antenna element separation is about half wavelength in order to avoid the appearance of grating lobes. On the other hand, recent developments in wireless communications have favoured the use of portable devices that utilize compact arrays with antenna element separations of less than half wavelength. Performance evaluation of DOA estimation algorithms employing compact arrays is an important and fundamental issue, but it has not been fully studied. In this paper, the performance of the matrix pencil method (MPM) that applies to DOA estimations is investigated through Monte Carlo simulations. The results show that closely spaced emitters can be accurately resolved using linear compact array with an array aperture as small as around half wavelength.

scholarly journals Central DOA Estimation Method for Exponential-Type Coherent Distributed Source Based on Fourth-Order Cumulant

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Hao Li ◽  
Weijia Cui ◽  
Bin Ba ◽  
Haiyun Xu ◽  
Yankui Zhang
Keyword(s):  
Fourth Order ◽  
Exponential Type ◽  
Complexity Analysis ◽  
Estimation Method ◽  
Doa Estimation ◽  
Estimation Accuracy ◽  
Distributed Source ◽  
Sparse Array ◽  
Fourth Order Cumulant ◽  
Array Aperture

The performance of direction-of-arrival (DOA) estimation for sparse arrays applied to the distributed source is worse than that applied to the point source model. In this paper, we introduce the coprime array with a large array aperture into the DOA estimation algorithm of the exponential-type coherent distributed source. In particular, we focus on the fourth-order cumulant (FOC) of the received signal which can provide more useful information when the signal is non-Gaussian than when it is Gaussian. The proposed algorithm extends the array aperture by combining the sparsity of array space domain with the fourth-order cumulant characteristics of signals, which improves the estimation accuracy and degree of freedom (DOF). Firstly, the signal-received model of the sparse array is established, and the fourth-order cumulant matrix of the received signal of the sparse array is calculated based on the characteristics of distributed sources, which extend the array aperture. Then, the virtual array is constructed by the sum aggregate of physical array elements, and the position set of its maximum continuous part array element is obtained. Finally, the center DOA estimation of the distributed source is realized by the subspace method. The accuracy and DOF of the proposed algorithm are higher than those of the distributed signal parameter estimator (DSPE) algorithm and least-squares estimation signal parameters via rotational invariance techniques (LS-ESPRIT) algorithm when the array elements are the same. Complexity analysis and numerical simulations are provided to demonstrate the superiority of the proposed method.

scholarly journals DOA estimation method of spatial spectrum product for distributed coprime linear array

2021 ◽  
Vol 39 (5) ◽  
pp. 1130-1138
Author(s):  
Na WANG ◽  
Xuanzhi ZHAO ◽  
Zengli LIU ◽  
Jingjing ZHANG
Keyword(s):  
Estimation Method ◽  
Doa Estimation ◽  
Spatial Spectrum ◽  
Estimation Accuracy ◽  
Low Snr ◽  
Distributed Array ◽  
Coprime Arrays ◽  
Coprime Array ◽  
Mathematical Derivation ◽  
Better Than

Coprime array isAsparse array composed of two uniform linear arrays with different spacing. When the two subarrays are inAnon-coherent distributed configuration, the direction of arrival (DOA) method based on the covariance analysis of the complete coprime array is no longer effective. According to the essential attribute that the distance between the elements of two subarrays can eliminate the angle ambiguity, based on the mathematical derivation, Aspatial spectral product DOA estimation method for incoherent distributed coprime arrays is proposed. Firstly, the spatial spectrum of each subarray is calculated by using the snapshot data of each subarray, and then the DOA estimation is realized by multiplying the spatial spectrum of each subarray. The simulation results show that the estimation accuracy and angle resolution of the present method are better than those of the traditional ambiguity resolution methods, and the estimation performance is good in the mutual coupling and low SNR environment, with the good adaptability and stability. Moreover, by using the flexibility of distributed array, the matching error is effectively solved through the rotation angle.

scholarly journals A Novel Designed Sparse Array for Noncircular Sources with High Degree of Freedom

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Yan-kui Zhang ◽  
Hai-yun Xu ◽  
Da-ming Wang ◽  
Bin Ba ◽  
Si-yao Li
Keyword(s):  
Design Method ◽  
Doa Estimation ◽  
Degree Of Freedom ◽  
Estimation Accuracy ◽  
Sparse Array ◽  
Array Configuration ◽  
Virtual Array ◽  
Array Aperture ◽  
Coprime Array ◽  
High Degree

The existing coprime array is mainly applicable to circular sources, while the virtual array degree of freedom (DOF) for noncircular sources is enhanced limitedly. In order to perfect the array DOF and the direction of arrival (DOA) estimation accuracy, a high degree of freedom sparse array design method for noncircular sources is put forward. Firstly, the method takes the advantages of the characteristic of the noncircular sources to expand the array manifold and then explores and solves the location distribution of the physical array sensors on the basis of the virtual array model with the help of the searching approach. The array configuration can obtain the longest continuous virtual array. The comparisons between the proposed array configuration and the common array configurations are advanced. The simulation experiments show that the sparse array presented in this paper can effectively increase the continuous virtual array aperture of noncircular sources, improve the array DOF and DOA estimation accuracy, and achieve the purpose of better estimation of multiple DOAs in underdetermined conditions.

scholarly journals Non-circular signal DOA estimation based on coprime array MIMO radar

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Fei Zhang ◽  
Chuantang Ji ◽  
Zijing Zhang ◽  
Dayu Yin ◽  
Yi Wang
Keyword(s):  
Doa Estimation ◽  
Mimo Radar ◽  
Degree Of Freedom ◽  
Estimation Methods ◽  
Two Dimensional ◽  
Phase Ambiguity ◽  
Music Algorithm ◽  
Array Aperture ◽  
Coprime Array ◽  
Signal Doa Estimation

AbstractAiming at the problems of low degree of freedom, small array aperture, and phase ambiguity in traditional coprime array direction-of-arrival estimation methods, a non-circular signal DOA estimation method based on expanded coprime array MIMO radar is proposed. Firstly, this method combines the coprime array and the MIMO radar to form transmitter and receiver array. Secondly, the array is expanded using the non-circular signal characteristics to reconstruct the received signal matrix. Then the dimensionality reduction is performed. The two-dimensional spectral peak search is converted into an optimization problem, and the optimization of the two-dimensional MUSIC algorithm is reconstructed using constraints, and a cost function is constructed to solve the problem. In addition, use the power series of the noise eigenvalues to correct the noise subspace to further improve the accuracy of the algorithm. Finally, the problem of no phase ambiguity in the method in this article is derived. Simulation experiments show that the method in this article can effectively avoid phase ambiguity, greatly improve the degree of freedom, and expand the array aperture. Compared with the traditional MUSIC algorithm and the mutual prime array MUSIC algorithm, it has better resolution and DOA estimation accuracy.

scholarly journals Fast DOA Estimation Based on the Transform Domain Weighted Noise Subspace Fitting Algorithm for Generalized Sparse Array

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Chunxi Liu ◽  
Zhikun Chen ◽  
Dongliang Peng
Keyword(s):  
Estimation Method ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Transform Domain ◽  
Music Algorithm ◽  
Sparse Array ◽  
Estimation Algorithms ◽  
Noise Subspace ◽  
Fitting Algorithm ◽  
Array Aperture

Compared with uniform arrays, a generalized sparse array (GSA) can obtain larger array aperture because of its larger element spacing, which improves the accuracy of DOA estimation. At present, most DOA estimation algorithms are only suitable for the uniform arrays, while a few DOA estimate algorithms that can be applied to the GSA are unsatisfactory in terms of computational speed and accuracy. To compensate this deficiency, an improved DOA estimation algorithm which can be applied to the GSA is proposed in this paper. First, the received signal model of the GSA is established. Then, a fast DOA estimation method is derived by combining the weighted noise subspace algorithm (WNSF) with the concept of “transform domain” (TD). Theoretical analysis and simulation results show that compared with the traditional multiple signal classification (MUSIC) algorithm and the traditional WNSF algorithm, the proposed algorithm has higher accuracy and lower computational complexity.

scholarly journals Partial Dictionary Based Off-Grid DOA Estimation Using Combined Coprime and Nested Array

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Jianfeng Li ◽  
Xiong Xu ◽  
Ping Li ◽  
Qiting Zhang
Keyword(s):  
Angular Resolution ◽  
State Of The Art ◽  
Estimation Method ◽  
Doa Estimation ◽  
Estimation Accuracy ◽  
Reconstruction Method ◽  
Phase Ambiguity ◽  
Virtual Array ◽  
Coprime Array ◽  
Cyclic Phase

A partial dictionary based direction of arrival (DOA) estimation method which addresses the off-grid problem and exploits combined coprime and nested array (CCNA) is proposed. Compared to general coprime array, CCNA yields two sparse coprime subarrays in the coarray domain by adding a third subarray in the physical-array domain. To ensure the DOA estimation performance, the subarray with larger aperture is chosen, and the cyclic phase ambiguity caused by the sparse subarray allows partial dictionary covering arbitrary cycle to represent the whole atoms, and then, the off-grid sparse reconstruction method is developed to amend the grid mismatch. After the sparse recovery and off-grid compensation, ambiguous DOA estimations can be eliminated by substituting the estimations into the whole virtual array. Multiple simulations verify that the proposed algorithm outperforms the other state-of-the-art methods in terms of DOA estimation accuracy and angular resolution.

scholarly journals Direction-of-Arrival Estimation for Coprime Array Using Compressive Sensing Based Array Interpolation

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Aihua Liu ◽  
Qiang Yang ◽  
Xin Zhang ◽  
Weibo Deng
Keyword(s):  
Covariance Matrix ◽  
Degrees Of Freedom ◽  
Linear Array ◽  
Estimation Method ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Interpolation Algorithm ◽  
Estimation Performance ◽  
Sample Covariance ◽  
Coprime Array

A method of direction-of-arrival (DOA) estimation using array interpolation is proposed in this paper to increase the number of resolvable sources and improve the DOA estimation performance for coprime array configuration with holes in its virtual array. The virtual symmetric nonuniform linear array (VSNLA) of coprime array signal model is introduced, with the conventional MUSIC with spatial smoothing algorithm (SS-MUSIC) applied on the continuous lags in the VSNLA; the degrees of freedom (DoFs) for DOA estimation are obviously not fully exploited. To effectively utilize the extent of DoFs offered by the coarray configuration, a compressing sensing based array interpolation algorithm is proposed. The compressing sensing technique is used to obtain the coarse initial DOA estimation, and a modified iterative initial DOA estimation based interpolation algorithm (IMCA-AI) is then utilized to obtain the final DOA estimation, which maps the sample covariance matrix of the VSNLA to the covariance matrix of a filled virtual symmetric uniform linear array (VSULA) with the same aperture size. The proposed DOA estimation method can efficiently improve the DOA estimation performance. The numerical simulations are provided to demonstrate the effectiveness of the proposed method.

scholarly journals Non-circular Signal DOA Estimation based on Coprime Array MIMO Radar

2021 ◽  
Author(s):  
Fei Zhang ◽  
Chuantang Ji ◽  
Zijing Zhang ◽  
Dayu Yin ◽  
Yi Wang
Keyword(s):  
Doa Estimation ◽  
Mimo Radar ◽  
Degree Of Freedom ◽  
Estimation Methods ◽  
Two Dimensional ◽  
Phase Ambiguity ◽  
Music Algorithm ◽  
Array Aperture ◽  
Coprime Array ◽  
Signal Doa Estimation

Abstract Aiming at the problems of low degree of freedom, small array aperture, phase ambiguity and other problems of traditional coprime array direction of arrival estimation methods, a non-circular signal DOA estimation method based on expanded coprime array MIMO radar is proposed. Firstly, this method combines the coprime array and the MIMO radar to form transmitter and receiver array. Secondly, the array is expanded using the non-circular signal characteristics to reconstruct the received signal matrix. Then the dimensionality reduction is performed. The two-dimensional spectral peak search is converted into an optimization problem, and the optimization of the two-dimensional MUSIC algorithm is reconstructed using constraints, and a cost function is constructed to solve the problem. In addition, using the power series of the noise eigenvalues to correct the noise subspace to further improve the accuracy of the algorithm. Finally, the problem of no phase ambiguity in the method in this article is derived. Simulation experiments show that the method in this article can effectively avoid phase ambiguity, greatly improve the degree of freedom, and expand the array aperture. Compared with the traditional MUSIC algorithm and the mutual prime array MUSIC algorithm, it has better resolution and DOA estimation accuracy.

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