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6th International Conference on Information Communication and Signal Processing, ICICSP 2023

作者： Yang, Jie Wang, Ya'nan Wang, Hanwei Northwestern Polytechnical University Shaanxi Key Laboratory of Underwater Information Technology Xi'an China

ISBN: (纸本)9798350339994

This paper aims at formulating a hierarchical Bayesian framework and variational inference perspective for direction-of-arrival (DOA) estimation using nested array. An overcomplete basis model of the array covariance vectors is constructed first to exploit the spatial sparsity of the incident signals. Then we utilize a three-stage hierarchical prior to model the sparsity of the unknown signal, and derive the estimation procedure with this prior using variational inference for fully Bayesian estimation. Finally, we conduct numerical simulations to demonstrate the performance of the proposed method in DOA estimation precision as compared with other state-of-the-art algorithms. © 2023 IEEE.

关键词： Direction-of-arrival(DOA) estimation Hierarchical prior nested array Variational inference

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Dilated Fractal nested array on Moving Platform

Dilated Fractal Nested Array on Moving Platform

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2021 CIE International Conference on Radar, Radar 2021

作者： Zhou, Mengwei Qin, Guodong Chen, Duofang School of Electronic Engineering Xidian University Xian China School of Life Science and Technology Xidian University Xian China

ISBN: (纸本)9781665498142

A novel dilated fractal nested array is proposed to improve the degrees of freedom on moving platform by combining the sparse fractal array and the dilated nested array. The proposed array can be used in the scenario of large array aperture. The closed-form expression of the sensor positions of the proposed array is presented. The translation factor is given and proved to obtain a fully filled difference coarray of the synthetic array. It is shown that the degree of freedom of the proposed array is greatly enhanced. Meanwhile, the proposed array has large aperture with less mutual coupling. © 2021 IEEE.

关键词： array motion difference coarray fractal array nested array Sparse array

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Non-Circular Signal DOA Estimation with nested array via Off-Grid Sparse Bayesian Learning

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SENSORS 2023年第21期23卷 8907-8907页

作者： Dong, Xudong Zhao, Jun Sun, Meng Zhang, Xiaofei Nanjing Univ Aeronaut & Astronaut Coll Elect & Informat Engn Nanjing 211106 Peoples R China Tongji Univ Coll Elect & Informat Engn Shanghai 201804 Peoples R China

For the traditional uniform linear array (ULA) direction of arrival (DOA) estimation method with a limited array aperture, a non-circular signal off-grid sparse Bayesian DOA estimation method based on nested arrays is proposed. Firstly, the extended matrix of the received data is constructed by taking advantage of the fact that the statistical properties of non-circular signals are not rotationally invariant. Secondly, we use the difference and sum co-arrays for the nested array technique, thus increasing the array aperture and improving the estimation accuracy. Finally, we take the noise as part of the interest signal and iteratively update the grid points using the sparse Bayesian learning (SBL) method to eliminate the modeling errors caused by off-grid gaps. The simulation results show that the proposed algorithm can improve the accuracy of DOA estimation compared with the existing algorithms.

关键词： off-grid sparse Bayesian learning DOA estimation non-circular signal nested array

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Two-Stage nested array Direction of Arrival Estimation for Mixed Signals

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SENSORS 2022年第14期22卷 5435-5435页

作者： Li, Wanru Deng, Ke Xi An Jiao Tong Univ Fac Elect & Informat Engn Xian 710049 Peoples R China

In this paper, a novel two-stage subspace-based direction of arrival (DOA) estimation algorithm with the nested array is proposed for mixed signals containing circular and non-circular ones. By exploiting the difference between the two types of steering vectors, the DOAs of circular signals are estimated in the first stage. After eliminating the estimated information of circular signals by the covariance matrix reconstruction and oblique projection methods, the dimensions of the noise subspace are increased in estimating the DOAs of non-circular signals in the second stage. Through the two-stage estimation, the DOAs of the circular and non-circular signals are estimated separately and different types of signals with similar or the same DOAs can be distinguished. Furthermore, to avoid the two-dimensional (2-D) search with huge computational burden, a one-dimensional (1-D) search method exploiting the rank deficiency is proposed in the DOA estimation for non-circular signals. The simulation results show that the proposed algorithm can effectively improve the estimation accuracy and resolution probability, especially when circular and non-circular signals have similar DOAs.

关键词： mixed signals nested array sum-difference co-array oblique projection

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Localization for mixed far-field and near-field sources utilizing improved symmetric nested array

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DIGITAL SIGNAL PROCESSING 2020年 107卷 102879-102879页

作者： Shen, Jiajun Zhou, Tian Xu, Chao Zhang, Wanyuan Du, Weidong Harbin Engn Univ Acoust Sci & Technol Lab Harbin 150001 Peoples R China Harbin Engn Univ Key Lab Marine Informat Acquisit & Secur Minist Ind & Informat Technol Harbin 150001 Peoples R China Harbin Engn Univ Coll Underwater Acoust Engn Harbin 150001 Peoples R China

nested arrays exhibit higher spatial resolution (SR) and enhanced degrees-of-freedom (DOFs) with fewer sensors, and they have been utilized for direction-of-arrival (DOA) estimation of both far-field (FF) and near-field (NF) sources. In this study, an improved symmetric nested array configuration with a given number of sensors was developed, which achieved increased consecutive and unique lags and thus resolved more targets than the actual number of inherent array sensors. In particular, the analytical expressions of the number of consecutive lags, the number of unique lags, and the virtual array aperture were derived for quantitative evaluation and comparison, as well as the corresponding array composition parameters of the optimal array geometry were obtained. In the mixed sources localization scheme, a special cumulant matrix was constructed to eliminate the range parameter in the NF steer vectors by exploiting the symmetric feature. Both subspace and sparse reconstruction techniques were exploited in order to directly obtain the DOAs of both FF and NF sources. With the estimated DOAs and the covariance matrix of the array output, the NF sources could be identified, and the corresponding range parameters could also be obtained by a one-dimension (1-D) spectrum search scheme. Numerous simulation results demonstrated that the proposed array showed a remarkable performance in terms of estimation accuracy, SR capacity, and numerous DOFs compared to state-of-the-art symmetric nested arrays. (C) 2020 Elsevier Inc. All rights reserved.

关键词： nested array Mixed sources localization Fourth-order cumulant Compressed sensing Degrees-of-freedom

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A Novel Generalized nested array MIMO Radar for DOA Estimation with Increased Degrees of Freedom and Low Mutual Coupling

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SENSORS 2024年第12期24卷 3952页

作者： Yang, Zhongtian Bi, Zhengyang Chen, Ye Hao, Honghao Beihang Univ Sch Energy & Power Engn Beijing 102200 Peoples R China Xian Jiaotong Liverpool Univ Coll Adv Technol Suzhou 215000 Peoples R China Nanjing Univ Aeronaut & Astronaut Coll Elect Informat Engn Nanjing 210016 Peoples R China

In array signal processing, the mutual coupling among physical sensors can inevitably affect the estimation of the direction of arrival (DOA). Despite the fact that multiple-input and multiple-output (MIMO) radar can provide greater degrees of freedom (DOFs), the influence of mutual coupling is largely overlooked in many current MIMO radar designs. To tackle this issue, we propose the utilization of a generalized nested array (GNA) in transmitter array and we introduce an expansion factor into the nested array in the receiver array. Thereby, a novel GNA-MIMO radar is put forward. The proposed MIMO radar offers O(N4) consecutive DOFs with N sensors and avoids the adverse effects of high mutual coupling caused by closely located sensors. Furthermore, we derive the closed-form expressions for the position of physical sensors and the attainable consecutive DOFs of the proposed MIMO radar. Through simulation experiments, we demonstrate the superior accuracy of the proposed MIMO configuration in DOA estimation and angle resolution under the condition of mutual coupling effect.

关键词： multiple-input multiple-output (MIMO) radar nested array direction of arrival estimation degree of freedom mutual coupling

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Sparse nested array with aperture extension for high accuracy angle estimation

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SIGNAL PROCESSING 2020年 176卷 107700-107700页

作者： He, Jin Zhang, Zenghui Shu, Ting Yu, Wenxian Shanghai Jiao Tong Univ Sch Elect Informat & Elect Engn Shanghai Key Lab Intelligent Sensing & Recognit Shanghai 200240 Peoples R China

Sparse nested arrays (SNAs) are presented for highly accurate angle estimation. A nested array is sparse if its sensor-spacing of the first level is extended beyond a half-wavelength. Each array grid is equipped with an identical two-component subarray, such as a half-wavelength spaced doublet, a spatiallycolocated p-u probe and a spatially-orthogonal dipole/loop pair, to solve angle ambiguities caused by aperture extension. (C) 2020 Elsevier B.V. All rights reserved.

关键词： nested array Sparse array Angle estimation Aperture extension

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Direct Position Determination of Coherently Distributed Sources based on Compressed Sensing with a Moving nested array

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KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS 2019年第5期13卷 2454-2468页

作者： Zhang Yankui Xu Haiyun Ba Bin Zong Rong Wang Daming Li Xiangzhi Natl Digital Syst Engn & Technol Res R&D Ctr Zhengzhou 450001 Henan Peoples R China

The existing direct position determinations(DPD) for coherently distributed(CD) sources are mostly applicable for uniform linear array(ULA), which result in a low degree of freedom(DOF), and it is difficult for them to realize the effective positioning in underdetermined condition. In this paper, a novel DPD algorithm for coherently distributed sources based on compressed sensing with a moving nested array is present. In this algorithm, the nested array is introduced to DPD firstly, and a positioning model of signal moving station based on nested array is constructed. Owing to the features of coherently distributed sources, the cost function of compressed sensing is established based on vectorization. For the sake of convenience, unconstrained transformation and convex transformation of cost functions are carried out. Finally, the position coordinates of the distribution source signals are obtained according to the theory of optimization. At the same time, the complexity is analyzed, and the simulation results show that, in comparison with two-step positioning algorithms and subspace-based algorithms, the proposed algorithm effectively solves the positioning problem in underdetermined condition with the same physical element number.

关键词： Direct position determinations(DPD) nested array distributed source compressed sensing vectorization

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Shifted super transformed nested array for DOA estimation of non-circular signals with increased uDOFs and reduced mutual coupling

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SIGNAL PROCESSING 2024年 221卷

作者： Li, Jiajie Chen, Hua Liu, Wei Zhu, Minghong Wang, Qing Wang, Gang Ningbo Univ Fac Elect Engn & Comp Sci Ningbo 315211 Peoples R China Zhejiang Key Lab Mobile Network Applicat Technol Ningbo 315211 Peoples R China Queen Mary Univ London Sch Elect Engn & Comp Sci London E1 4NS England Tianjin Univ Sch Elect Informat Engn Tianjin 300072 Peoples R China

In this work, a scheme for array structure design is proposed to maximize uniform degrees of freedom (uDOFs) and reduce mutual coupling. It starts by exchanging the positions of two subarrays within the nested array, followed by mitigating mutual coupling through sensor relocation due to the dense subarray, and ultimately increasing uDOFs by globally shifting the entire array to the right. Following this scheme, the concept of Shifted Super Transformed nested array (SSTNA) is introduced and general guidelines for the construction of SSTNA are provided. Analytical expressions for the continuous region of the virtual apertures and uDOFs are derived. Furthermore, the optimal shifting parameter and the first three weight functions are determined for SSTNA. Theoretical analysis shows that SSTNA can effectively reduce mutual coupling while maintaining high uDOFs. In strong mutual coupling scenarios, simulation results are provided to demonstrate the effectiveness and superiority of the proposed design.

关键词： nested array Direction of arrival estimation Non-circular Mutual coupling Uniform degrees of freedom

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Underdetermined Direction of Arrival Estimation of Non-Circular Signals via Matrix Completion in nested array

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IEEE ACCESS 2019年 7卷 183717-183728页

作者： Han, Peng Wang, Daming Cui, Weijia Zhang, Jin Natl Digital Switching Syst Engn & Technol Res Ct Zhengzhou 450001 Peoples R China

Direction-of-arrival (DOA) estimation using nested linear array ignores the information from repeated sensors, thus involves the problem of losing accuracy. Moreover, non-circular feature of signals is rarely considered and it results in discontinuity of the virtual array, namely, holes appear. This paper first provide an improved data averaging method to increase the accuracy of DOA estimation by fusing data from covariance and elliptic covariance. And then an algorithm based on matrix completion theory in nested array that greatly extends the degrees of freedom (DOF) and is able to find more sources than number of physical sensors is presented. The algorithm reconstructs the covariance matrix of the virtual linear array, which exactly has the same shift invariance as the uniform linear array but a higher aperture. Considering about the missing elements of the virtual array covariance matrix, we apply matrix completion theory to solve the problem. Finally, true DOAs of multiple signals can be obtained through subspace algorithms. Numerical results demonstrate that the proposed algorithms can obtain high accuracy while underdetermined DOA estimation is realized.

关键词： Direction-of-arrival nested array matrix completion theory data averaging

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