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A Third-Order Sparse array Design Scheme Based on Second-Order sum-difference co-array Analysis

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2025年第4期74卷 6108-6120页

作者： Guo, Haodong Chen, Hua Yang, Songjie Liu, Wei Yuen, Chau So, Hing Cheung Ningbo Univ Fac Elect Engn & Comp Sci Ningbo 315211 Peoples R China Univ Elect Sci & Technol China Natl Key Lab Wireless Commun Chengdu 610054 Peoples R China Hong Kong Polytech Univ Dept Elect & Elect Engn Hong Kong Peoples R China Nanyang Technol Univ Sch Elect & Elect Engn Singapore City 639798 Singapore Univ Hong Kong Dept Elect Engn City SAR Hong Kong Peoples R China

Recently, non-conventional odd-order statistics, especially the third-order cumulants (TOCs), have been introduced to direction-of-arrival (DOA) estimation based on third-order nested array (TONA). compared with the methods employing second-order statistics, it significantly increases the number of uniform degrees-of-freedom (uDOFs), which can even be comparable to the fourth-order cumulant approach with a small number of array elements. In this paper, through analysis of the second-order sum-difference co-array, a third-order sparse linear array (SLA) design scheme suitable for TOCs is proposed, which can extend the commonly used second-order SLAs to the third-order, and prototype arrays are analyzed along with their closed-form expressions. It is shown that by selecting an appropriate generator array, the derived third-order SLA has far more uDOFs than the existing TONA, and also reduces the mutual coupling effect. In addition, a strategy is developed to mitigate the mutual coupling effect further by mirror-flipping some elements of the dense segment. The proposed array design scheme balances high uDOFs and low mutual coupling, greatly improving its robustness as well as DOA estimation accuracy.

关键词： Mutual coupling Vectors Sensor arrays Estimation Prototypes Direction-of-arrival estimation Manifolds Matrix converters Closed-form solutions Accuracy DOA estimation mutual coupling sparse linear array sum-difference co-array third-order cumulant (TOC)

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Spatially Smoothed Tensor-Based Method for Bistatic co-Prime MIMO Radar With Hole-Free sum-difference co-array

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IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2022年第4期71卷 3889-3899页

作者： Lai, Xin Zhang, Xiaofei Zheng, Wang Ma, Penghui Nanjing Univ Aeronaut & Astronaut Coll Elect & Informat Engn Nanjing 210016 Peoples R China Nanjing Univ Aeronaut & Astronaut Minist Ind & Informat Technol Key Lab Dynam Cognit Syst Electromagnet Spectrum Nanjing 211106 Peoples R China Purple Mt Labs Nanjing 210016 Peoples R China

In this paper, we investigate the problem of joint direction of departure (DoD) and direction of arrival (DoA) estimation with bistatic MIMO radar. Specifically, a weaved co-prime array (WCA) bistatic MIMO (WCA-bMIMO) radar is proposed to produce a hole-free sum-difference co-array, which enables to offer significantly increased degrees of freedom (DoFs) and enlarged array aperture. Moreover, the two-dimensional spatial smoothing method is introduced to construct a smoothed received signal, which helps to tackle the rank deduction problem rooted in the equivalent one-snapshot received signal from the sum-difference co-array. Subsequently, the joint DoD and DoA estimates can be obtained by extracting the three-way tensor model. Furthermore, co-array Cramer-Rao Bound (CRB) for the bistatic co-prime MIMO radar is provided. Finally, the superiorities of the proposed bistatic co-prime MIMO radar in accuracy and resolution are proved by numerical simulation results.

关键词： Sensors Sensor arrays MIMO radar Estimation Radar Direction-of-arrival estimation array signal processing co-prime array bistatic MIMO radar sum-difference co-array DoD and DoA estimation Cramer-Rao Bound spatial smoothing

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Non-circular signals for nested array: sum-difference co-array and direction of arrival estimation algorithm

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IET RADAR SONAR AND NAVIGATION 2020年第1期14卷 27-35页

作者： Wang Yunfei Shen Jinqing Zhang Xiaofei He Yi Dai Xiangrui Nanjing Univ Aeronaut & Astronaut Coll Elect & Informat Engn Nanjing 210016 Peoples R China Southeast Univ State Key Lab Millimeter Waves Nanjing 210096 Peoples R China Southeast Univ Natl Mobile Commun Res Lab Nanjing 210096 Peoples R China

Nested array has aroused remarkable attention due to the capability to obtain both enhanced degrees of freedom (DOFs) and enlarged array aperture, whereas only difference co-array is employed. Here, the authors construct the sum co-array of nested array by utilising the non-circular (NC) characteristic and, subsequently, the sum-difference (SD) co-array is obtained by careful crafting of the sum co-array and the typical difference co-array, which doubles the resulting co-array aperture and, simultaneously, further increases the achievable DOF compared with the difference co-array of nested array. Moreover, to circumvent the time-consuming two-dimensional spectral search, the authors proposed the reduced-dimension multiple signals classification (MUSIC) algorithm with the SD (SD-RD-MUSIC) co-array of the nested array by discarding the NC phase. Resultantly, the proposed SD-RD-MUSIC co-array algorithm can resolve more signals and obtain more accurate direction of arrival estimates. In addition, the effectiveness and superiority of the proposed method are validated by numerical simulations.

关键词： array signal processing direction-of-arrival estimation signal classification nested array sum-difference co-array sum co-array typical difference co-array co-array algorithm noncircular signals direction of arrival estimation DOA estimation algorithm enhanced degrees of freedom co-array aperture enlarged array aperture two-dimensional spectral search reduced-dimension multiple signals classification MUSIC algorithm SD-RD-MUSIC co-array algorithm

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Transformed Nested array Designed for DOA Estimation of Non-Circular Signals: Reduced sum-difference co-array Redundancy Perspective

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IEEE coMMUNICATIONS LETTERS 2020年第6期24卷 1262-1265页

作者： Wang, Yunfei Wu, Wei Zhang, Xiaofei Zheng, Wang Nanjing Univ Aeronaut & Astronaut Coll Elect & Informat Engn Nanjing 211106 Peoples R China Nanjing Univ Aeronaut & Astronaut Minist Ind & Informat Technol Key Lab Dynam Cognit Syst Electromagnet Spectrum Nanjing 211106 Peoples R China

In this letter, we investigate the issue of sparse array design for direction of arrival (DOA) estimation of non-circular (NC) signals, and propose the transformed nested array (TNA) which reduces overlapping virtual sensors between the difference and the sum co-array generated by the conventional nested array (NA) and can thus obtain a sum-difference co-array with higher degrees of freedom (DOFs). From the co-array redundancy perspective, we construct the TNA via two operations. The first is to exchange positions of the two subarrays of NA in order to redistribute its sum co-array to separate overlapping virtual sensors. The second is to split the dense subarray into two parts and relocate one of them aiming to further decrease redundant virtual sensors and enlarge the virtual array aperture as well. Theoretical results and numerical simulations are provided to assess the superiority of the proposed configuration.

关键词： Sensor arrays Redundancy Direction-of-arrival estimation Estimation Apertures Sonar navigation sum-difference co-array degree of freedom virtual array aperture DOA estimation non-circular signal

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Underdetermined DOA Estimation Using Unfold coprime array From the Perspective of sum-difference co-array

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IEEE ACCESS 2019年 7卷 168557-168564页

作者： Zhao, Pinjiao Wang, Ke Hu, Guobing Wan, Liangtian Jinling Inst Technol Dept Elect & Informat Engn Nanjing 211169 Peoples R China Yangtze Univ Natl Demonstrat Ctr Expt Elect & Elect Educ Jingzhou 434023 Peoples R China Dalian Univ Technol Sch Software Key Lab Ubiquitous Network & Serv Software Liaoni Dalian 116620 Peoples R China

Direction-of-Arrival (DOA) estimation with sparse non-uniform linear arrays (SNLAs) has recently attracted a growing concern for the reason that more sources than the number of physical sensors can be resolved as compared with the conventional uniform linear arrays (ULAs). In this paper, we develop an underdetermined DOA estimation method using unfold coprime array (unfold CPA) from the perspective of sum-difference co-array (SDCA). By jointly using the temporal and spatial information of the impinging sources and the Khatri-Rao (KR) product operation, the SDCA of the unfold CPA are obtained, which can provide more consecutive DOF and larger array aperture than the SNLAs based on the difference co-array (DCA). Additionally, benefitting from the array configuration of the unfold CPA, the weight functions of the physical sensor pairs with small separations are equal to zero, thus the mutual coupling effects between sensors are reduced significantly. The theoretical propositions and numerical simulations are provided to confirm the effectiveness and superior performance of the proposed method.

关键词： Underdetermined DOA estimation unfold coprime array sum-difference co-array degrees of freedom

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Non-Circular Sources DOA Estimation for coprime array With Impulsive Noise: A Novel Augmented Phased Fractional Low-Order Moment

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IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2022年第10期71卷 10559-10569页

作者： Dong, Xudong Zhang, Xiaofei Zhao, Jun Sun, Meng Nanjing Univ Aeronaut & Astronaut Coll Elect & Informat Engn Nanjing 210000 Peoples R China Key Lab Dynam Cognit Syst Electromagnet Spectrum Nanjing 210000 Jiangsu Peoples R China Tongji Univ Coll Elect & Informat Engn Shanghai 201800 Peoples R China

The coprime array has become an essential part of array signal processing, which can obtain a much higher degrees of freedom (DOFs) and larger aperture than that of the conventional approaches. However, this technique is applied in the ideal condition with white Gaussian noise. In this paper, we propose to extend the coprime array to the practical communication scenario by taking impulsive noise and non-circular signals into account. An augmented phased fractional low-order moment (A-PFLOM) is proposed to suppress impulsive noise, and then reduced-dimension MUSIC (RD-MUSIC) subspace techniques are applied for direction of arrival (DOA) information of non-circular sources. compared to the existing methods, the proposed method has better estimation performance in a wide range of impulsive noise environments.

关键词： Estimation Direction-of-arrival estimation Phased arrays array signal processing Signal processing algorithms Sun Multiple signal classification Direction of arrival (DOA) coprime array non-circular (NC) signal phased fractional low-order moment (PFLOM) sum-difference co-array

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Sparse array Design for DOA Estimation of Non-Circular Signals: Reduced co-array Redundancy and Increased DOF

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IEEE SENSORS JOURNAL 2021年第24期21卷 27928-27937页

作者： Zhang, Xiaofei Lai, Xin Zheng, Wang Wang, Yunfei Nanjing Univ Aeronaut & Astronaut Coll Elect & Informat Engn Nanjing 210016 Peoples R China Nanjing Univ Aeronaut & Astronaut Key Lab Dynam Cognit Syst Electromagnet Spectrum Minist Ind & Informat Technol Nanjing Peoples R China Purple Mt Labs Nanjing 211100 Peoples R China

In the past decade, sparse arrays have aroused considerable attention for the ability to provide larger array aperture, more degrees of freedom (DOFs) and better estimation performance compared with the uniform linear array (ULA). In this paper, the problem of sparse array design is investigated for direction of arrival (DOA) estimation of non-circular (NC) signals, where both the difference co-array (DCA) and sum co-array (SCA) of physical array configuration can be utilized. Specifically, we first introduce a sliding array strategy which moves the array along the axis as a whole in order to reduce the co-array redundancy and enhance the consecutive DOFs of the sum-difference co-array (SDCA). Subsequently, we focus on the SCA of the conventional nested array (NA) and propose an approach which increases the DOFs of the SCA by relocating proper sensors. Furthermore, based on the above strategy and approach, we derive an extended sliding nested array (ESNA) with few redundant virtual sensors and an enhanced SCA, which can offer increased consecutive DOFs, enlarged virtual array aperture (VAA) and can thus bring high angle estimation accuracy of NC signals. Finally, analytic solutions and simulation results are given to validate the superiority of the proposed ESNA in terms of DOFs and estimation performance.

关键词： Sensor arrays Estimation Direction-of-arrival estimation array signal processing Redundancy covariance matrices Signal processing algorithms DOA estimation non-circular signal sparse array sum-difference co-array co-array redundancy degree of freedom

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Padded Sparse array for DoA Estimation of Noncircular Signals in the Presence of Unknown Mutual coupling

Padded Sparse Array for DoA Estimation of Noncircular Signal...

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IEEE International Symposium on Antennas and Propagation / USNC-URSI Radio Science Meeting (IEEE APS/URSI)

作者： Yan, Hangqi Wang, Yuexian Wang, Ling Northwestern Polytech Univ Sch Elect & Informat Xian 710072 Peoples R China

ISBN: (纸本)9781946815101

Recently, sparse arrays are widely studied for circular signals, but the characteristics of non-circular signals are rarely considered in array design. Besides, mutual coupling effect between elements cannot be ignored. A new padded array configuration is designed for non-circular signals in this paper. Simulation results show that the proposed geometry provide better accuracy for DOA estimation in the presence of unknown mutual coupling while preserving high degrees of freedom.

关键词： Noncircular signals mutual coupling PMISC arrays sum-difference co-array DOA estimation.

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DOA Estimation via an Augmented Unfolded coprime MIMO configuration of Transceiver Reversal with Enhanced Degrees of Freedom

DOA Estimation via an Augmented Unfolded Coprime MIMO Config...

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2021 CIE International conference on Radar, Radar 2021

作者： Zhang, Yule Hu, Guoping Zhu, Mingming You, Zhiyuan Ren, Mingjian Lin, Bin Graduate College Air Force Engineering University Xi'an China Air and Missile Defense College Air Force Engineering University Xi'an China

ISBN: (纸本)9781665498142

This paper proposes an augmented unfolded coprime MIMO configuration of transceiver reversal, where the transmitter adopts an augmented unfolded coprime array, and the layout of the receiver is obtained by flipping the transmitter. From the perspective of the sum-difference co-array (SDCA), the closed-form expressions for the range of consecutive lags, the number of discrete lags and the degrees of freedom (DOF) are derived. Moreover, the sparse reconstruction method of interpolated virtual elements is employed for direction of arrival (DOA) estimation. compared with the conventional coprime MIMO configuration, the proposed MIMO can provide more DOF and larger virtual aperture. Simulation results verify the superior performance of the proposed MIMO configuration. © 2021 IEEE.

关键词： augmented unfolded coprime array degrees of freedom DOA estimation MIMO radar sum-difference co-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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