scholarly journals 2D-DOA Estimation for Cylindrical Array with Mutual Coupling

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Hao Feng ◽  
Lutao Liu ◽  
Biyang Wen
Keyword(s):  
Mutual Coupling ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Coupling Matrix ◽  
Estimation Algorithms ◽  
Conformal Array ◽  
Signal Parameters ◽  
2D Doa Estimation ◽  
Two Parameter ◽  
Cylindrical Array

Most conventional direction-of-arrival (DOA) estimation algorithms are affected by the effect of mutual coupling, which make the performance of DOA estimation degrade. In this paper, a novel DOA estimation algorithm for conformal array in the presence of unknown mutual coupling is proposed. The special mutual coupling matrix (MCM) is applied to eliminate the effect of mutual coupling. With suitable array design, the decoupling between polarization parameter and angle information is accomplished. The two-demission DOA (2D-DOA) estimation is finally achieved based on estimation of signal parameters via rotational invariance techniques (ESPRIT). The proposed algorithm can be extended to conical conformal array as well. Two parameter pairing methods are illustrated for cylindrical and conical conformal array, respectively. The computer simulation verifies the effectiveness of the proposed algorithm.

scholarly journals An Efficient 2-D DOA Estimation for a Cylindrical Conformal Array with Unknown Mutual Coupling

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Chao Liu ◽  
Shunian Yin
Keyword(s):  
Mutual Coupling ◽  
Coupling Effect ◽  
Doa Estimation ◽  
Coupling Coefficients ◽  
Rotation Invariant ◽  
Rank Reduction ◽  
Estimation Algorithms ◽  
Conformal Array ◽  
Signal Parameters ◽  
Finding Method

The limited space of a conformal array may lead to a serious mutual coupling effect, which will significantly affect the performance of direction of arrival (DOA) estimation algorithms. In this paper, an efficient 2-D direction finding method is developed in the presence of unknown mutual coupling for the uniform cylindrical conformal array (CCA). To avoid the time-consuming two-dimensional spectral peak searching, the 2-D DOA estimation is decoupled and divided into two 1-D DOA estimations. Elevation is first estimated based on a subarray estimation of signal parameters via rotation invariant technique (ESPRIT), and then azimuth is estimated based on the rank reduction (RARE) method by using the elevation estimation result. Consequently, the mutual coupling coefficients can be estimated after getting the DOA estimates. The proposed method can well calibrate the mutual coupling effect of a cylindrical array with a low computational complexity. The final simulation results corroborate our analysis.

scholarly journals 2D-DOA and Mutual Coupling Estimation in Vehicle Communication System via Conformal Array

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Yan Zou ◽  
Hong Xie ◽  
Liangtian Wan ◽  
Guangjie Han ◽  
Wei Li
Keyword(s):  
Intelligent Transportation Systems ◽  
Mutual Coupling ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Transportation Systems ◽  
Coupling Coefficients ◽  
Vehicle Communication ◽  
Estimation Algorithms ◽  
Conformal Array ◽  
The Matrix

Many direction-of-arrival (DOA) estimation algorithms have been proposed recently. However, the effect of mutual coupling among antenna elements has not been taken into consideration. In this paper, a novel DOA and mutual coupling coefficient estimation algorithm is proposed in intelligent transportation systems (ITS) via conformal array. By constructing the spectial mutual coupling matrix (MCM), the effect of mutual coupling can be eliminated via instrumental element method. Then the DOA of incident signals can be estimated based on parallel factor (PARAFAC) theory. The PARAFAC model is constructed in cumulant domain using covariance matrices. The mutual coupling coefficients are estimated based on the former DOA estimation and the matrix transformation between MCM and the steering vector. Finally, due to the drawback of the parameter pairing method in Wan et al., 2014, a novel method is given to improve the performance of parameter pairing. The computer simulation verifies the effectiveness of the proposed algorithm.

scholarly journals Joint Estimation of 2D-DOA and Frequency Based on Space-Time Matrix and Conformal Array

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Liang-Tian Wan ◽  
Lu-Tao Liu ◽  
Wei-Jian Si ◽  
Zuo-Xi Tian
Keyword(s):  
Estimation Algorithm ◽  
Doa Estimation ◽  
Joint Estimation ◽  
Conformal Array ◽  
Joint Frequency ◽  
Estimate Frequency ◽  
Performance Deterioration ◽  
2D Doa Estimation ◽  
Parallel Factor ◽  
Suppress Noise

Each element in the conformal array has a different pattern, which leads to the performance deterioration of the conventional high resolution direction-of-arrival (DOA) algorithms. In this paper, a joint frequency and two-dimension DOA (2D-DOA) estimation algorithm for conformal array are proposed. The delay correlation function is used to suppress noise. Both spatial and time sampling are utilized to construct the spatial-time matrix. The frequency and 2D-DOA estimation are accomplished based on parallel factor (PARAFAC) analysis without spectral peak searching and parameter pairing. The proposed algorithm needs only four guiding elements with precise positions to estimate frequency and 2D-DOA. Other instrumental elements can be arranged flexibly on the surface of the carrier. Simulation results demonstrate the effectiveness of the proposed algorithm.

scholarly journals Blind Direction-of-Arrival Estimation with Uniform Circular Array in Presence of Mutual Coupling

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Song Liu ◽  
Lisheng Yang ◽  
Shizhong Yang ◽  
Qingping Jiang ◽  
Haowei Wu
Keyword(s):  
Mutual Coupling ◽  
Coupling Parameter ◽  
Direction Of Arrival ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Estimation Methods ◽  
Circular Array ◽  
Signal Parameters ◽  
Simulation Results ◽  
Parameter Estimation Methods

A blind direction-of-arrival (DOA) estimation algorithm based on the estimation of signal parameters via rotational invariance techniques (ESPRIT) is proposed for a uniform circular array (UCA) when strong electromagnetic mutual coupling is present. First, an updated UCA model with mutual coupling in a discrete Fourier transform (DFT) beam space is deduced, and the new manifold matrix is equal to the product of a centrosymmetric diagonal matrix and a Vandermonde-structure matrix. Then we carry out blind DOA estimation through a modified ESPRIT method, thus avoiding the need for spatial angular searching. In addition, two mutual coupling parameter estimation methods are presented after the DOAs have been estimated. Simulation results show that the new algorithm is reliable and effective especially for closely spaced signals.

scholarly journals High Accuracy 2D-DOA Estimation for Conformal Array Using PARAFAC

2014 ◽  
Vol 2014 ◽  
pp. 1-14 ◽  
Author(s):  
Liangtian Wan ◽  
Weijian Si ◽  
Lutao Liu ◽  
Zuoxi Tian ◽  
Naixing Feng
Keyword(s):  
Data Model ◽  
Doa Estimation ◽  
Polarization Parameter ◽  
Estimation Algorithms ◽  
Conformal Array ◽  
Parafac Model ◽  
Array Structures ◽  
2D Doa Estimation ◽  
Parallel Factor ◽  
Cramer Rao Bound

Due to the polarization diversity (PD) of element patterns caused by the varying curvature of the conformal carrier, the conventional direction-of-arrival (DOA) estimation algorithms could not be applied to the conformal array. In order to describe the PD of conformal array, the polarization parameter is considered in the snapshot data model. The paramount difficulty for DOA estimation is the coupling between the angle information and polarization parameter. Based on the characteristic of the cylindrical conformal array, the decoupling between the polarization parameter and DOA can be realized with a specially designed array structure. 2D-DOA estimation of the cylindrical conformal array is accomplished via parallel factor analysis (PARAFAC) theory. To avoid parameter pairing problem, the algorithm forms a PARAFAC model of the covariance matrices in the covariance domain. The proposed algorithm can also be generalized to other conformal array structures and nonuniform noise scenario. Cramer-Rao bound (CRB) is derived and simulation results with the cylindrical conformal array are presented to verify the performance of the proposed algorithm.

scholarly journals DOA Estimation for Coprime Linear Array Based on MI-ESPRIT and Lookup Table

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 3043 ◽  
Author(s):  
Weike Zhang ◽  
Xi Chen ◽  
Kaibo Cui ◽  
Tao Xie ◽  
Naichang Yuan
Keyword(s):  
Linear Array ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Spatial Spectrum ◽  
Angle Measurement ◽  
Lookup Table ◽  
Signal Parameters ◽  
Estimation Precision ◽  
Simulation Results ◽  
The Relationship

In order to improve the angle measurement performance of a coprime linear array, this paper proposes a novel direction-of-arrival (DOA) estimation algorithm for a coprime linear array based on the multiple invariance estimation of signal parameters via rotational invariance techniques (MI-ESPRIT) and a lookup table method. The proposed algorithm does not require a spatial spectrum search and uses a lookup table to solve ambiguity, which reduces the computational complexity. To fully use the subarray elements, the DOA estimation precision is higher compared with existing algorithms. Moreover, the algorithm avoids the matching error when multiple signals exist by using the relationship between the signal subspace of two subarrays. Simulation results verify the effectiveness of the proposed algorithm.

2D DOA Estimation Using Sparse Representation of Higher-Order Power of Covariance Matrix

2014 ◽  
Vol 998-999 ◽  
pp. 779-783
Author(s):  
Zheng Luo ◽  
Fei Yu ◽  
Lin Wu ◽  
Yuan Liu
Keyword(s):  
Covariance Matrix ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Higher Order ◽  
Eigenvalue Decomposition ◽  
Coherent Signals ◽  
Sparse Decomposition ◽  
Sparse Signal Representation ◽  
2D Doa Estimation ◽  
Source Signals

A novel two-dimensional (2D) direction-of-arrival (DOA) estimation algorithm utilizing a sparse signal representation of higher-order power of covariance matrix is proposed. Through applying the higher-order power of covariance matrix to construct a new sparse decomposition vector, this algorithm avoids the estimation of incident signal number and eigenvalue decomposition. And the hierarchical granularity-dictionary is studied, which forms the over-complete dictionary adaptively in the light of source signals’ distribution. Compared with MUSIC and L1-SVD, this algorithm not only provides a better 2D DOA performance but also possesses the capability of coherent signals estimation. Theoretical analysis and simulation results demonstrate the validity and robust of the proposed algorithm.

scholarly journals 2D DOA Estimation with a Two-Parallel Array Consisting of Two Uniform Large-Spacing Linear Arrays

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Sheng Liu ◽  
Jing Zhao ◽  
Yu Zhang
Keyword(s):  
Mutual Coupling ◽  
Elevation Angle ◽  
Doa Estimation ◽  
Matrix Product ◽  
Linear Arrays ◽  
Parallel Array ◽  
Propagator Method ◽  
The Matrix ◽  
2D Doa Estimation ◽  
Estimation Precision

In this paper, an improved propagator method (PM) is proposed by using a two-parallel array consisting of two uniform large-spacing linear arrays. Because of the increase of element spacing, the mutual coupling between two sensors can be reduced. Firstly, two matrices containing elevation angle information are obtained by PM. Then, by performing EVD of the product of the two matrices, the elevation angles of incident signals can be estimated without direction ambiguity. At last, the matrix product is used again to obtain the estimations of azimuth angles. Compared with the existed PM algorithms based on conventional uniform two-parallel linear array, the proposed PM algorithm based on the large-spacing linear arrays has higher estimation precision. Many simulation experiments are presented to verify the effect of proposed scheme in reducing the mutual coupling and improving estimation precision.

scholarly journals Codebook-Aided DOA Estimation Algorithms for Massive MIMO System

Electronics ◽  
2018 ◽  
Vol 8 (1) ◽  
pp. 26 ◽  
Author(s):  
Shufeng Li ◽  
Hongda Wu ◽  
Libiao Jin
Keyword(s):  
Massive Mimo ◽  
Large Scale ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Computational Cost ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Frame Structure ◽  
Green Communication ◽  
Estimation Algorithms

The conventional direction of arrival (DOA) estimation algorithm is not effective with the tremendous complexity due to the large-scale array antennas in a massive multiple-input multiple-output (MIMO) system. A new frame structure for downlink transmission is presented. Then, codebook-aided (C-aided) algorithms are proposed based on this frame structure that can fully exploit the priori information under channel codebook feedback mechanism. An oriented angle range is scoped through the codebook feedback, which is drastically beneficial to reduce computational burden for DOA estimation in massive MIMO systemss. Compared with traditional DOA estimation algorithms, our proposed C-aided algorithms are computationally efficient and meet the demand of future green communication. Simulations show the estimation effectiveness of C-aided algorithms and advantage for decrement of computational cost.

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