scholarly journals Improved 2D Coprime Array Structure with the Difference and Sum Coarray Concept

Electronics ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. 273
Author(s):  
Guiyu Wang ◽  
Zesong Fei ◽  
Shiwei Ren ◽  
Xiaoran Li
Keyword(s):  
Closed Form ◽  
Degrees Of Freedom ◽  
Spatial Information ◽  
Temporal Information ◽  
Direction Of Arrival Estimation ◽  
One Dimensional ◽  
Sparse Arrays ◽  
Array Structure ◽  
The Difference ◽  
Coprime Array

Recently, the difference and sum (diff-sum) coarray has attracted much attention in one-dimensional direction-of-arrival estimation for its high degrees-of-freedom (DOFs). In this paper, we utilize both the spatial information and the temporal information to construct the diff-sum coarray for planar sparse arrays. The diff-sum coarray contains both the difference coarray and the sum coarray, which provides much higher DOFs than the difference coarray alone. We take a planar coprime array consisting of two uniform square subarrays as the array model. To fully use the aperture-extending ability of the diff-sum coarray, we propose two novel configurations to improve the planar coprime array. The first configuration compresses the inter-element spacing of one subarray and results in a larger consecutive area in the coarray. The second configuration rearranges the two subarrays and introduces a proper separation between them, which can significantly reduce the redundancy of the diff-sum coarray and increase the DOFs. Besides, we derive the closed-form expressions of the central consecutive ranges in the coarrays of the proposed array configurations. Simulations verify the superiority of the proposed array configurations.

scholarly journals Design of Novel Nested Arrays Based on the Concept of Sum-Difference Coarray

Electronics ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 115
Author(s):  
Weijian Si ◽  
Zhanli Peng ◽  
Changbo Hou ◽  
Fuhong Zeng
Keyword(s):  
Closed Form ◽  
Degrees Of Freedom ◽  
Spatial Information ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Temporal Information ◽  
Index Sets ◽  
Simulation Results ◽  
Nested Arrays ◽  
The Relationship

Nested arrays have recently attracted considerable attention in the field of direction of arrival (DOA) estimation owing to the hole-free property of their virtual arrays. However, such virtual arrays are confined to difference coarrays as only spatial information of the received signals is exploited. By exploiting the spatial and temporal information jointly, four kinds of novel nested arrays based on the sum-difference coarray (SDCA) concept are proposed. To increase the degrees of freedom (DOFs) of SDCA, a modified translational nested array (MTNA) is introduced first. Then, by analyzing the relationship among sensors in MTNA, we give the specific positions of redundant sensors and remove them later. Finally, we derive the closed-form expressions for the proposed arrays as well as their SDCAs. Meanwhile, different index sets corresponding to the proposed arrays are also designed for their use in obtaining the desirable SDCAs. Moreover, the properties regarding DOFs of SDCAs and physical apertures for the proposed arrays are analyzed, which prove that both the DOFs and physical apertures are improved. Simulation results are provided to verify the superiority of the proposed arrays.

scholarly journals Increasing Utilization of Redundant Virtual Array for DOA Estimation Based on Coprime Array

2020 ◽  
Vol 2020 ◽  
pp. 1-7
Author(s):  
Chenghong Zhan ◽  
Guoping Hu ◽  
Zixin Zhang ◽  
Ziang Feng
Keyword(s):  
Parameter Estimation ◽  
High Precision ◽  
Degrees Of Freedom ◽  
Doa Estimation ◽  
Far Field ◽  
Virtual Array ◽  
Previous Algorithm ◽  
Array Structure ◽  
Simulation Results ◽  
Coprime Array

In this paper, we initiated a method to estimate the direction of arrival (DOA) of far-field, narrowband, and incoherent targets using coprime array. First, we proposed a coprime array structure and analysed the distribution of difference coarray (DCA). The degrees of freedom (DOF) of the proposed coprime array became clearer by referring to the DCA conception. However, previous algorithm only uses the continuous virtual array, which causes the virtual array elements in the repeated position being abandoned. Therefore, the paper analyses the distribution of virtual array based on DCA conception and averages the receiving signal on these redundant virtual array elements to increase the utilization of receiving data. As a result, the algorithm has high precision in parameter estimation. Simulation results have shown the superiority of the proposed algorithm.

scholarly journals DOA estimation based on sum–difference coarray with virtual array interpolation concept

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Yarong Ding ◽  
Shiwei Ren ◽  
Weijiang Wang ◽  
Chengbo Xue
Keyword(s):  
Numerical Simulation ◽  
Degrees Of Freedom ◽  
Doa Estimation ◽  
Superior Performance ◽  
Norm Minimization ◽  
Atomic Norm ◽  
Virtual Array ◽  
Simulation Results ◽  
The Difference ◽  
Coprime Array

AbstractThe sum–difference coarray is the union of difference coarray and the sum coarray, which is capable to obtain a higher number of degrees of freedom (DOF) than the difference coarray. However, this method fails to use all information provided by the coprime array because of the existence of holes. In this paper, we introduce the virtual array interpolation into the sum–difference coarray domain. After interpolating the virtual array, we estimate the DOA by reconstructing the covariance matrix to resolve an atomic norm minimization problem in a gridless way. The proposed method is gridless and can effectively utilize the DOF of a larger virtual array. Numerical simulation results verify the effectiveness and the superior performance of the proposed algorithm.

scholarly journals COPRIME ARRAY PARAMETERS OPTIMIZATION FOR DOA ESTIMATION

2021 ◽  
Vol 4 (2) ◽  
pp. 23-32
Author(s):  
Fatimah A. Salman ◽  
Bayan M. Sabbar
Keyword(s):  
Mutual Coupling ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Parameters Optimization ◽  
Degree Of Freedom ◽  
Direction Of Arrival Estimation ◽  
Sparse Arrays ◽  
Sparse Array ◽  
Simulation Results ◽  
Coprime Array

Sparse array such as the coprime array is one of the most preferable sparse arrays for direction of arrival estimation due to its properties, like simplicity, capability of resolving more sources than the number of elements and resistance to mutual coupling issue.  In this paper, a new coprime array model is proposed to increase the number of degree of freedom (DOF) and improve the performance of coprime array.   The new designed array can avoid the mutual coupling by minimizing the lag redundancy and expand the central lags in the virtual difference co-array. Thus, the propose structure can resolve more sources than the prototype coprime array using the same number of elements with improved direction of arrival estimation. Simulation results demonstrate that the proposed array model is more efficient than the others coprime array model.

scholarly journals DOA Estimation Based on Sum-Difference Coarray with Virtual Array Interpolation Concept

2021 ◽  
Author(s):  
Yarong Ding ◽  
Shiwei Ren ◽  
Weijiang Wang ◽  
Chengbo Xue
Keyword(s):  
Numerical Simulation ◽  
Degrees Of Freedom ◽  
Doa Estimation ◽  
Superior Performance ◽  
Norm Minimization ◽  
Atomic Norm ◽  
Virtual Array ◽  
Simulation Results ◽  
The Difference ◽  
Coprime Array

Abstract The sum-difference coarray is the union of difference coarray and the sum coarray, which is capable to obtain a higher number of degrees of freedom (DOF) than the difference coarray. However, this method fails to use all information provided by the coprime array because of the existence of holes. In this paper, we introduce the virtual array interpolation into the sum-difference coarray domain. After interpolating the virtual array, we estimate the DOA by reconstructing the covariance matrix to resolve an atomic norm minimization problem in a gridless way. The proposed method is gridless and can effectively utilize the DOF of a larger virtual array. Numerical simulation results verify the effectiveness and the superior performance of the proposed algorithm.

scholarly journals DOA Estimation of an Enhanced Generalized Nested Array with Increased Degrees of Freedom and Reduced Mutual Coupling

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Yule Zhang ◽  
Guoping Hu ◽  
Junpeng Shi ◽  
Hao Zhou ◽  
Chenghong Zhan ◽  
...  
Keyword(s):  
Degrees Of Freedom ◽  
Mutual Coupling ◽  
Doa Estimation ◽  
Superior Performance ◽  
Sparse Arrays ◽  
Single Antenna ◽  
Simulation Results ◽  
The Difference ◽  
Low Degrees ◽  
Special Case

Aiming at low degrees of freedom (DOF) and high mutual coupling (MC) of the existing sparse arrays, an enhanced generalized nested array (EGNA) is proposed in this paper. Specifically, the proposed array adds a single antenna on the basis of generalized nested array (GNA), and the difference of coprime factors is employed as the spacing between the second subarray and the additional antenna. Then, the values of the coprime factors are analyzed in detail, which indicates that Yang-NA can be explained as a special case. Compared with the majority of the existing sparse arrays, EGNA not only has the closed-form expressions of the physical antenna locations, consecutive lags, and unique lags, but also significantly increases DOF and reduces MC. In view of the above advantages, EGNA can obtain superior performance in direction of arrival (DOA) estimation. Numerical simulation results verify the rationality and superiority of the proposed nested array.

scholarly journals A Novel MIMO Array with Reduced Mutual Coupling and Increased Degrees of Freedom

2021 ◽  
Vol 2021 ◽  
pp. 1-6
Author(s):  
Mingxin Liu ◽  
Lin Zou ◽  
Haohao Ren ◽  
Xuelian Yu ◽  
Yun Zhou ◽  
...  
Keyword(s):  
Degrees Of Freedom ◽  
Mutual Coupling ◽  
Coupling Effect ◽  
Multiple Input Multiple Output ◽  
Fixed Number ◽  
Physical Sensors ◽  
Input Multiple Output ◽  
Physical Sensor ◽  
Array Structure ◽  
The Difference

In this paper, we consider the problem of array design for Multiple-Input Multiple-Output (MIMO) array under the condition of fixed number of physical sensors and mutual coupling. A novel MIMO array based on the second-order super nested transmit and receive arrays is proposed by using the difference coarray. It can obtain the closed form expressions for the physical sensor locations and the degrees of freedom (DOF) from any given number physical sensors. The proposed array structure can significantly enhance DOF and effectively decrease unknown mutual coupling effect. The effectiveness and superiority of the proposed MIMO array structure are verified from the number of DOF and MUSIC spectra by numerical simulations.

scholarly journals A Design Method of Sparse Array with High Degrees of Freedom Based on Fourth-Order Cumulants

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Fengtong Mei ◽  
Daming Wang ◽  
Chunxiao Jian ◽  
Yinsheng Wang ◽  
Weijia Cui
Keyword(s):  
Closed Form ◽  
Fourth Order ◽  
Degrees Of Freedom ◽  
Linear Array ◽  
Design Method ◽  
Doa Estimation ◽  
Closed Form Expression ◽  
Form Expression ◽  
Sparse Arrays ◽  
Non Gaussian

Recently, the design of sparse linear array for direction of arrival (DOA) estimation of non-Gaussian signals has attracted considerable interest due to the fact that the fourth-order difference coarray offered by non-Gaussian significantly increases the aperture of a virtual linear array, which improves the performance of DOA estimation. In this paper, a super four-level nested array (S-FL-NA) configuration based on fourth-order cumulants (FOC) is proposed. The S-FL-NA consists of uniform linear arrays which have different interelement spacing. The proposed array configuration is designed based on interelement spacing, which, for a given number of sensors, is uniquely determined by a closed-form expression. We also derive the closed-form expression for the degrees of freedom (DOFs) of the proposed array. The optimal distribution of the number of sensors in each uniform linear array of the proposed array is given for an arbitrary number of sensors. Compared with the existing sparse arrays, the proposed array can provide a higher number of degrees of freedom and a larger physical array aperture. In addition, to improve the calculation speed of the fourth-order cumulant matrix, we simplify the FOC matrix by removing some redundancy. Numerical simulations are conducted to verify the superiority of the S-FL-NA over other sparse arrays.

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