A New Atomic Norm for DOA Estimation With Gain-Phase Errors

Chen, Peng; Chen, Zhimin; Cao, Zhenxin; Wang, Xianbin

doi:10.1109/tsp.2020.3010749

Cited by 66 publications

(28 citation statements)

References 58 publications

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“…The algorithm of the position perturbation estimation is given in Algorithm 3, where 1 K ∈ R K×1 denotes a vector with all entries being 1. In the gradient descent method, the estimated position perturbation is updated by the gradient vector, as shown in (25), where the most critical part is to obtain the gradient vector. The following contents are about how to get the gradient vector.…”

Section: B the Gradient Descent Methods For Perturbation Estimationmentioning

confidence: 99%

Efficient DOA Estimation Method for Reconfigurable Intelligent Surfaces Aided UAV Swarm

Chen,

Zheng

et al. 2022

Preprint

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The conventional direction of arrival (DOA) estimation methods are performed with multiple receiving channels. In this paper, a changeling DOA estimation problem is addressed in a different scenario with only one full-functional receiving channel. A new unmanned aerial vehicle (UAV) swarm system using multiple lifted reconfigurable intelligent surface (RIS) is proposed for the DOA estimation. The UAV movement degrades the DOA estimation performance significantly, and the existing atomic norm minimization (ANM) methods cannot be used in the scenario with array perturbation. Specifically, considering the position perturbation of UAVs, a new atomic norm-based DOA estimation method is proposed, where an atomic norm is defined with the parameter of the position perturbation. Then, a customized semi-definite programming (SDP) method is derived to solve the atomic norm-based method, where different from the traditional SDP method, an additional transforming matrix is formulated. Moreover, a gradient descent method is applied to refine the estimated DOA and the position perturbation further. Simulation results show that the proposed method achieves much better DOA estimation performance in the RIS-aided UAV swarm system with only one receiving channel than various benchmark schemes.

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Section: B the Gradient Descent Methods For Perturbation Estimationmentioning

confidence: 99%

Efficient DOA Estimation Method for Reconfigurable Intelligent Surfaces Aided UAV Swarm

Chen,

Zheng

et al. 2022

Preprint

Self Cite

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“…Besides, single antenna can only get the direction information of the targets without distance and other information. Instead, multiple arrays have the advantages of flexible beam control [6], higher spatial resolution [7] and higher signal gain [8]. Original two-step location technology needs to estimate the intermediate parameters from the original data, such as time of arrival (TOA) [9], time difference of arrival (TDOA) [10], angle of arrival (AOA) [11].…”

Section: Introductionmentioning

confidence: 99%

Direct Position Determination of Non-Circular Sources for Multiple Arrays via Weighted Euler ESPRIT Data Fusion Method

2022

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In recent years, direct position determination (DPD) with multiple arrays for non-circular (NC) signals is a hot topic to research. Conventional DPD techniques with spectral peak search methods have high computational complexity and are sensitive to the locations of the observation stations. Besides, there will be loss when the signal propagates in the air, which leads to different received signal-to-noise ratios (SNRs) for each observation station. To attack the problems mentioned above, this paper derives direct position determination of non-circular sources for multiple arrays via weighted Euler estimating signal parameters viarotational invariance techniques (ESPRIT) data fusion (NC-Euler-WESPRIT) method. Firstly, elliptic covariance information of NC signals and Euler transformation are used to extend the received signal. Secondly, ESPRIT is applied to avoid the high-dimensional spectral function search problem of each observation station. Then, we combine the information of all observation stations to construct a spectral function without complex multiplication to reduce the computational complexity. Finally, the data of each observation station is weighted to compensate for the projection error. The consequence of simulation indicates that the proposed NC-Euler-WESPRIT algorithm not only improves the estimation performance, but also greatly reduces the computational complexity compared with subspace data fusion (SDF) technology and NC-ESPRIT algorithm.

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“…To obtain the signal direction, the direction of arrival (DOA) estimation methods have been studied for decades [8]- [10]. The sparse reconstruction-based methods have been proposed to improve the estimation performance [11]- [13].…”

Section: Introductionmentioning

confidence: 99%

Reconfigurable Intelligent Surface Aided Sparse DOA Estimation Method With Non-ULA

Chen¹,

Yang²,

Chen³

et al. 2021

IEEE Signal Process. Lett.

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The direction of arrival (DOA) estimation problem is addressed in this paper. A reconfigurable intelligent surface (RIS) aided system for the DOA estimation is proposed. Unlike traditional DOA estimation systems, a low-cost system with only one complete functional receiver is given by changing the phases of the reflected signals at the RIS elements to realize the multiple measurements. Moreover, an atomic norm-based method is proposed for the DOA estimation by exploiting the target sparsity in the spatial domain and solved by a semidefinite programming (SDP) method. Furthermore, the RIS elements can be any geometry array for practical consideration, so a transformation matrix is formulated and different from the conventional SDP method. Simulation results show that the proposed method can estimate the DOA more accurately than the existing methods in the non-uniform linear RIS array.

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A New Atomic Norm for DOA Estimation With Gain-Phase Errors

Cited by 66 publications

References 58 publications

Efficient DOA Estimation Method for Reconfigurable Intelligent Surfaces Aided UAV Swarm

Efficient DOA Estimation Method for Reconfigurable Intelligent Surfaces Aided UAV Swarm

Direct Position Determination of Non-Circular Sources for Multiple Arrays via Weighted Euler ESPRIT Data Fusion Method

Reconfigurable Intelligent Surface Aided Sparse DOA Estimation Method With Non-ULA

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