Results 1 to 10 of about 35,203 (149)
Two-Dimensional Direction-of-Arrival Fast Estimation of Multiple Signals with Matrix Completion Theory in Coprime Planar Array [PDF]
Sensors, 2018 In estimating the two-dimensional (2D) direction-of-arrival (DOA) using a coprime planar array, the main issues are the high complexity of spectral peak search and the limited degree of freedom imposed by the number of sensors.
Haiyun Xu +4 more
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Generalized and symmetric coprime planar array for direction of arrival estimation
IET Radar, Sonar & Navigation, 2022 Degrees of freedom and mutual coupling are two important factors to determine the ability of direction of arrival (DOA) estimation. Although coprime planar array (CPPA) has less mutual coupling than hourglass array (HA) and ladder array (LA), its ...
Ming Jian Ren +3 more
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Two-Dimensional DOA Estimation for Coprime Planar Arrays: From Array Structure Design to Dimensionality-Reduction Root MUSIC Algorithm [PDF]
SensorsThis paper proposes a novel sparse array design and an efficient algorithm for two-dimensional direction-of-arrival (2D-DOA) estimation. By analyzing the hole distribution in coprime arrays and introducing supplementary elements, we design a ...
Yunhe Shi +2 more
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IEEE Access, 2018 Generally, a coprime planar array (CPA) incorporates two uniform planar subarrays with large inter-element spacing to achieve improved direction of arrival (DOA) estimation performance, where the two subarrays are usually interleaved in the same quadrant.
Wang Zheng +3 more
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IEEE Access, 2018 In this paper, the problem of 2-D direction-of-arrival (2-D-DOA) estimation for coprime planar arrays is investigated, and a method based on the polynomial root finding technique with high accuracy and computational efficiency is proposed.
Dong Zhang +5 more
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A High Resolution Optimum 2D Coprime Planar Array [PDF]
2022 IEEE 19th India Council International Conference (INDICON), 2022 Designing a new class of rectangular two-dimensional sparse array to enhance the signal resolving capabilities with a limited number of sensors has always been a challenge. We explore the non-uniformity of the sparse arrays to enhance the Degrees of Freedom (DOF) by considering the under-determined cases using the concept of the virtual array.
Goel, Kretika +2 more
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Two-Dimensional DOA Estimation for Coprime Planar Arrays Based on Self-Correlation Tensor
Mathematical Problems in Engineering, 2022 In the coprime planar array (CPA), the existing tensor DOA estimation has the problem that the statistics are not fully utilized. We propose a two-dimensional DOA estimation method based on tensor self-correlation, which realizes the high-resolution and high-precision joint estimation of elevation angle and azimuth angle.
Hao Li +4 more
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ETRI Journal, 2023 In this study, the problem of blind signal separation for coprime planar arrays is investigated. For coprime planar arrays comprising two uniform rectangular subarrays, we link the signal separation to the tensor-based model called coupled canonical ...
Zhongyuan Que +2 more
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Fast Two-Dimensional Direction-of-Arrival Estimation of Multiple Signals in Coprime Planar Array [PDF]
Journal of Sensors, 2019 Two-dimensional direction-of-arrival (DOA) estimation in coprime planar array involves problems that the complexity of spectral peak search is huge and the noncircular feature of signals is not considered. Considering that unitary estimating signal parameters via rotational invariance techniques (Unitary-ESPRIT) is a low complexity subspace algorithm ...
Haiyun Xu +4 more
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Computationally Efficient Ambiguity-Free Two-Dimensional DOA Estimation Method for Coprime Planar Array: RD-Root-MUSIC Algorithm [PDF]
Mathematical Problems in Engineering, 2020 While the two-dimensional (2D) spectral peak search suffers from expensive computational burden in direction of arrival (DOA) estimation, we propose a reduced-dimensional root-MUSIC (RD-Root-MUSIC) algorithm for 2D DOA estimation with coprime planar array (CPA), which is computationally efficient and ambiguity-free.
Luo Chen, Changbo Ye, Baobao Li
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