Article
Engineering, Electrical & Electronic
Jianfeng Li, Yi He, Penghui Ma, Xiaofei Zhang, Qihui Wu
Summary: This paper discusses a new array geometry (SNACD) for DOA estimation, which combines the properties of nested array and coprime array, achieving good performance in both co-array and physical-array domains. The proposed scheme outperforms existing methods in terms of DOA estimation accuracy, angular resolution, and mutual coupling influence. Multiple simulations are provided to demonstrate the effectiveness of the approach.
IEEE SENSORS JOURNAL
(2021)
Article
Engineering, Electrical & Electronic
Xin Lai, Xiaofei Zhang, Wang Zheng, Jianfeng Li, Fuhui Zhou
Summary: In this paper, a new array configuration called the fragmented coprime array with optimal inter-subarray spacing (FCAOIS) is proposed. FCAOIS maximizes the intra-subarray spacing of a fragmented coprime array (FCA) and incorporates two interlayer subarrays into the FCA, improving the performance of the difference coarray. Simulation results demonstrate the advantages of FCAOIS over other sparse arrays in mitigating mutual coupling and increasing the scale of uniform difference coarray.
Article
Engineering, Electrical & Electronic
Zhe Peng, Yingtao Ding, Shiwei Ren, Haixia Wu, Weijiang Wang
Summary: This letter introduces the application of sparse arrays in array signal processing. A new sparse array, coprime nested array, is proposed, which achieves the same number of uniform degrees of freedom as the prototype nested array while reducing mutual coupling effect. The effectiveness of the proposed configurations is verified through numerical simulations.
IEEE SIGNAL PROCESSING LETTERS
(2022)
Article
Computer Science, Information Systems
Navid Amani, Feike Jansen, Alessio Filippi, Marianna Ivashina, Rob Maaskant
Summary: A novel sparse automotive MIMO radar configuration is proposed for low-complexity super-resolution single snapshot DOA estimation. The configuration incorporates physical antenna effects and uses spatial smoothing algorithm and co-prime array principle to suppress temporal correlation among sources and avoid DOA ambiguities, leading to enhanced spatial resolution.
Article
Engineering, Electrical & Electronic
Yang Xu, Zhi Zheng, Wen-Qin Wang
Summary: In this paper, a robust DOA estimation algorithm is proposed for a nested array with unknown mutual coupling. The algorithm derives a coarray signal model without mutual coupling, builds a block sparse representation of the coarray signal, and formulates a simplified block sparse recovery problem for DOA estimation. The algorithm utilizes all coarray outputs and reduces the influence of mutual coupling, outperforming existing techniques according to numerical results.
CIRCUITS SYSTEMS AND SIGNAL PROCESSING
(2023)
Article
Engineering, Electrical & Electronic
Fengtong Mei, Haiyun Xu, WeiJia Cui, Chunxiao Jian, Jian Zhang
Summary: In this paper, a super transformed nested array (STNA) is proposed for the direction of arrival (DOA) estimation of non-circular signals, which effectively alleviates the high mutual coupling problem. The advantages of the STNA are demonstrated through numerical simulations.
IET RADAR SONAR AND NAVIGATION
(2022)
Article
Engineering, Electrical & Electronic
Ahmed M. A. Shaalan, Jun Du, Yan-Hui Tu
Summary: This paper introduces a new linear sparse array layout, called dilated nested array (DNA), which has features including a closed-form expression for sensor locations, a large central uniform linear array segment, and fewer sensor pairs with small separations. It effectively reduces mutual coupling effects and improves array performance.
IEEE TRANSACTIONS ON SIGNAL PROCESSING
(2022)
Article
Environmental Sciences
Yuqing Zhao, Feng Shen, Biqing Qi, Zhen Meng
Summary: A sparse reconstruction approach based on a coprime array of antennas is proposed in this paper to provide reliable DOA estimation under GNSS spoofing attack. By exploiting the self-coherence property of genuine satellite signals and spoofing, a denoised covariance matrix is constructed for DOA estimation.
Article
Engineering, Electrical & Electronic
Yuzhang Guo, Jie Jin, Qing Wang, Hua Chen, Wei Liu
Summary: This study proposes a novel data-driven method to solve the mutual coupling problem between antenna array elements and improve parameter estimation performance. Simulation results demonstrate that the proposed approach significantly outperforms existing methods.
Article
Geochemistry & Geophysics
Wanxin Shi, Qian He, Huanhuan Wu
Summary: This article discusses the importance of joint direction of arrival (DOA) and Doppler frequency estimation in radar and wireless communication systems, as well as the need to design the array structure and sampling method to improve estimation performance in real applications with limited antennas and snapshots. The authors propose the use of coprime array and coprime sampler to address this issue. They introduce the concept of generalized spatial-temporal coprime sampling (GSTCS), which allows different temporal sampling parameters for the coprime samplers at different antennas. Through optimization of the spatial coprime array and temporal coprime sampler parameters, the authors demonstrate improved degrees of freedom (DOFs) and estimation performance using compressed sensing (CS) theory.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2023)
Article
Computer Science, Information Systems
Fengtong Mei, Haiyun Xu, Weijia Cui, Bin Ba, Yinsheng Wang
Summary: The paper introduces a coprime array with shifted and flipped sub-array for the DOA estimation of non-circular signals, achieving a higher number of consecutive lags and reducing the number of sensor pairs with small separation. Closed-form expression for the number of consecutive lags, optimal distribution of two sub-arrays, and weight function are derived, and numerical simulations demonstrate the superiority of the proposed array over existing sparse arrays.
Article
Engineering, Electrical & Electronic
Dimitris G. Chachlakis, Tongdi Zhou, Fauzia Ahmad, Panos P. Markopoulos
Summary: Coprime arrays enable increased DoA estimation of sources by optimizing coarray autocorrelation estimation performance with Minimum-MSE method. Numerical evaluation shows that this approach provides superior autocorrelation estimates, leading to improved DoA estimation performance.
DIGITAL SIGNAL PROCESSING
(2021)
Article
Engineering, Electrical & Electronic
Guojun Jiang, Yunlong Yang
Summary: In order to improve the performance of direction of arrival (DOA) estimation, a synthetic sparse nested array with dual-polarization antennas is proposed. A cascade method composed of three steps is also presented for super-resolution angle estimation. The proposed array and method demonstrate superiority in high-accuracy DOA estimation in the presence of mutual coupling, as shown by theoretical analysis and simulation results.
Article
Chemistry, Analytical
Yang Liu, Na Dong, Xiaohui Zhang, Xin Zhao, Yinghui Zhang, Tianshuang Qiu
Summary: This paper proposes a sparse Bayesian learning algorithm to solve the mutual coupling problem between antennas by modeling the array output signal vector with mutual coupling coefficients, and improves the accuracy of DOA estimation by grid refinement.
Article
Engineering, Electrical & Electronic
Nabil Mohsen, Ammar Hawbani, Xingfu Wang, Benjamin Bairrington, Liang Zhao, Saeed Alsamhi
Summary: In this article, two optimized shifted coprime arrays with sum-difference coarrays are proposed to reduce mutual coupling. The proposed array designs have closed-form expressions for their sensor locations and achievable degrees of freedom. Simulation results show that these arrays can achieve comparable degrees of freedom and OSCAwSDCa-II demonstrates more robustness against strong mutual coupling.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Engineering, Electrical & Electronic
Soo-Chang Pei, Chun-Lin Liu, Yun-Chiu Lai
IEEE TRANSACTIONS ON SIGNAL PROCESSING
(2016)
Article
Engineering, Electrical & Electronic
Chun-Lin Liu, P. P. Vaidyanathan
IEEE TRANSACTIONS ON SIGNAL PROCESSING
(2016)
Article
Engineering, Electrical & Electronic
Chun-Lin Liu, Palghat P. Vaidyanathan
IEEE TRANSACTIONS ON SIGNAL PROCESSING
(2017)
Article
Engineering, Electrical & Electronic
Chun-Lin Liu, P. P. Vaidyanathan
IEEE TRANSACTIONS ON SIGNAL PROCESSING
(2017)
Article
Engineering, Electrical & Electronic
Chun-Lin Liu, Palghat P. Vaidyanathan
IEEE TRANSACTIONS ON SIGNAL PROCESSING
(2019)
Article
Engineering, Electrical & Electronic
Chun-Lin Liu, Palghat P. Vaidyanathan
IEEE TRANSACTIONS ON SIGNAL PROCESSING
(2019)
Article
Engineering, Electrical & Electronic
Chun-Lin Liu, P. P. Vaidyanathan
Article
Engineering, Electrical & Electronic
Chun-Lin Liu
Summary: This paper proposes a coarray combination method for handling sensor failures in sparse arrays and addressing DOA estimation problems in array processing. By solving a convex optimization problem with prior knowledge of failure patterns, the optimal coarray combination matrix can be obtained, avoiding array diagnosis and improving the accuracy of DOA estimation.
IEEE SIGNAL PROCESSING LETTERS
(2022)
Article
Engineering, Electrical & Electronic
Yuan-Pon Chen, Chun-Lin Liu
Summary: In array processing, the paper investigates the lower and upper bounds of the size of the fourth-order difference co-array, proving that the ULA and exponential array achieve these boundaries. Additionally, the concept of fourth-order redundancy is introduced to quantify the efficiency of the ULA segment in the fourth-order difference co-array, providing further insights into its size.
IEEE SIGNAL PROCESSING LETTERS
(2021)
Proceedings Paper
Computer Science, Information Systems
Chun-Lin Liu, P. P. Vaidyanathan
2017 FIFTY-FIRST ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS, AND COMPUTERS
(2017)
Proceedings Paper
Engineering, Electrical & Electronic
Chun-Lin Liu, P. P. Vaidyanathan
2017 IEEE 7TH INTERNATIONAL WORKSHOP ON COMPUTATIONAL ADVANCES IN MULTI-SENSOR ADAPTIVE PROCESSING (CAMSAP)
(2017)
Proceedings Paper
Acoustics
Chun-Lin Liu, P. P. Vaidyanathan
2017 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP)
(2017)
Article
Engineering, Electrical & Electronic
Chun-Lin Liu, P. P. Vaidyanathan
DIGITAL SIGNAL PROCESSING
(2017)
Proceedings Paper
Computer Science, Information Systems
Chun-Lin Liu, P. P. Vaidyanathan
2016 50TH ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS AND COMPUTERS
(2016)