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

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.

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2D-DOA Estimation for Cylindrical Array with Mutual Coupling

Mathematical Problems in Engineering ◽

10.1155/2014/716978 ◽

2014 ◽

Vol 2014 ◽

pp. 1-8 ◽

Cited By ~ 2

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.

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

Mobile Information Systems ◽

10.1155/2015/841341 ◽

2015 ◽

Vol 2015 ◽

pp. 1-10 ◽

Cited By ~ 2

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.

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DOA Estimation Using Fourth-Order Cumulants in Nested Arrays with Structured Imperfections

Sensors ◽

10.3390/s20040994 ◽

2020 ◽

Vol 20 (4) ◽

pp. 994

Author(s):

Baoping Wang ◽

Junhao Zheng

Keyword(s):

Fourth Order ◽

Mutual Coupling ◽

Estimation Method ◽

Doa Estimation ◽

Coupling Model ◽

Coupling Coefficients ◽

Rank Reduction ◽

Phase Errors ◽

Reduction Property ◽

Nested Arrays

Recently developed super nested array families have drawn much attention owing to their merits on keeping the benefits of the standard nested arrays while further mitigating coupling in dense subarray portions. In this communication, a new mutual coupling model for nested arrays is constructed. Analyzing the structure of the newly formed mutual coupling matrix, a transformation of the distorted steering vector to separate angular information from the mutual coupling coefficients is revealed. By this property, direction of arrival (DOA) estimates can be determined via a grid search for the minimum of a determinant function of DOA, which is induced by the rank reduction property. We also extend the robust DOA estimation method to accommodate the unknown mutual coupling and gain-phase mismatches in the nested array. Compared with the schemes of super nested array families on reducing the mutual coupling effects, the solutions presented in this paper has two advantages: (a) It is applicable to the standard nested arrays without rearranging the configuration to increase the inter-element spacing, alleviating the cross talk in dense uniform linear arrays (ULAs) as well as gain-phase errors in sparse ULA parts; (b) Perturbations in nested arrays are estimated in colored noise, which is significant but rarely discussed before. Simulations results corroborate the superiority of the proposed methods using fourth-order cumulants.

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Direction Finding with Gain/Phase Errors and Mutual Coupling Errors in the Presence of Auxiliary Sensors

Mathematical Problems in Engineering ◽

10.1155/2014/429426 ◽

2014 ◽

Vol 2014 ◽

pp. 1-12 ◽

Cited By ~ 2

Author(s):

Weijian Si ◽

Di Wu ◽

Lutao Liu ◽

Xinggen Qu

Keyword(s):

Efficient Method ◽

Mutual Coupling ◽

Doa Estimation ◽

Direction Finding ◽

Coupling Coefficients ◽

Decoupling Method ◽

Estimation Algorithms ◽

Phase Errors ◽

Simulation Results ◽

Array Errors

Many classical direction of arrival (DOA) estimation algorithms suffer from sensitivity to array errors. A simple but efficient method is presented for direction finding in the presence of gain and phase errors as well as mutual coupling errors. By applying a group of auxiliary sensors, DOAs and gain and phase coefficients can be simultaneously estimated, and mutual coupling coefficients can also be estimated by utilizing a novel decoupling method. The proposed algorithm does not require iterative operation or any calibration sources or spectral peak searching. Simulation results demonstrate the effectiveness of the proposed method.

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Efficient Two-Dimensional Direction Finding Algorithm for Rectilinear Sources Under Unknown Mutual Coupling

Sensors ◽

10.3390/s20071914 ◽

2020 ◽

Vol 20 (7) ◽

pp. 1914

Author(s):

Jian Xie ◽

Qiuping Wang ◽

Yuexian Wang ◽

Xin Yang

Keyword(s):

Degrees Of Freedom ◽

Mutual Coupling ◽

Array Signal Processing ◽

Elevation Angle ◽

Doa Estimation ◽

Two Dimensional ◽

Rank Reduction ◽

Communication Signals ◽

Estimation Performance ◽

Direction Cosines

Digital communication signals in wireless systems may possess noncircularity, which can be used to enhance the degrees of freedom for direction-of-arrival (DOA) estimation in sensor array signal processing. On the other hand, the electromagnetic characteristics between sensors in uniform rectangular arrays (URAs), such as mutual coupling, may significantly deteriorate the estimation performance. To deal with this problem, a robust real-valued estimator for rectilinear sources was developed to alleviate unknown mutual coupling in URAs. An augmented covariance matrix was built up by extracting the real and imaginary parts of observations containing the circularity and noncircularity of signals. Then, the actual steering vector considering mutual coupling was reparameterized to make the rank reduction (RARE) property available. To reduce the computational complexity of two-dimensional (2D) spectral search, we individually estimated y-axis and x-axis direction-cosines in two stages following the principle of RARE. Finally, azimuth and elevation angle estimates were determined from the corresponding direction-cosines respectively. Compared with existing solutions, the proposed method is more computationally efficient, involving real-valued operations and decoupled 2D spectral searches into twice those of one-dimensional searches. Simulation results verified that the proposed method provides satisfactory estimation performance that is robust to unknown mutual coupling and close to the counterparts based on 2D spectral searches, but at the cost of much fewer calculations.

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Compressed Sensing-Based DOA Estimation with Unknown Mutual Coupling Effect

Electronics ◽

10.3390/electronics7120424 ◽

2018 ◽

Vol 7 (12) ◽

pp. 424 ◽

Cited By ~ 11

Author(s):

Peng Chen ◽

Zhenxin Cao ◽

Zhimin Chen ◽

Linxi Liu ◽

Man Feng

Keyword(s):

Compressed Sensing ◽

Mutual Coupling ◽

Linear Array ◽

State Of The Art ◽

Coupling Effect ◽

Estimation Method ◽

Doa Estimation ◽

System Model ◽

Reconstruction Problem ◽

Uniform Linear Array

The performance of a direction-finding system is significantly degraded by the imperfection of an array. In this paper, the direction-of-arrival (DOA) estimation problem is investigated in the uniform linear array (ULA) system with the unknown mutual coupling (MC) effect. The system model with MC effect is formulated. Then, by exploiting the signal sparsity in the spatial domain, a compressed-sensing (CS)-based system model is proposed with the MC coefficients, and the problem of DOA estimation is converted into that of a sparse reconstruction. To solve the reconstruction problem efficiently, a novel DOA estimation method, named sparse-based DOA estimation with unknown MC effect (SDMC), is proposed, where both the sparse signal and the MC coefficients are estimated iteratively. Simulation results show that the proposed method can achieve better performance of DOA estimation in the scenario with MC effect than the state-of-the-art methods, and improve the DOA estimation performance about 31.64 % by reducing the MC effect by about 4 dB.

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SBL-Based Direction Finding Method with Imperfect Array

Electronics ◽

10.3390/electronics7120426 ◽

2018 ◽

Vol 7 (12) ◽

pp. 426 ◽

Cited By ~ 4

Author(s):

Peng Chen ◽

Zhimin Chen ◽

Xuan Zhang ◽

Linxi Liu

Keyword(s):

Mutual Coupling ◽

Bayesian Learning ◽

Linear Array ◽

State Of The Art ◽

Coupling Effect ◽

Direction Finding ◽

Noise Variance ◽

Uniform Linear Array ◽

Unknown Parameters ◽

Finding Method

The imperfect array degrades the direction finding performance. In this paper, we investigate the direction finding problem in uniform linear array (ULA) system with unknown mutual coupling effect between antennas. By exploiting the target sparsity in the spatial domain, the sparse Bayesian learning (SBL)-based model is proposed and converts the direction finding problem into a sparse reconstruction problem. In the sparse-based model, the off-grid errors are introduced by discretizing the direction area into grids. Therefore, an off-grid SBL model with mutual coupling vector is proposed to overcome both the mutual coupling and the off-grid effect. With the distribution assumptions of unknown parameters including the noise variance, the off-grid vector, the received signals and the mutual coupling vector, a novel direction finding method based on SBL with unknown mutual coupling effect named DFSMC is proposed, where an expectation-maximum (EM)-based step is adopted by deriving the estimation expressions for all the unknown parameters theoretically. Simulation results show that the proposed DFSMC method can outperform state-of-the-art direction finding methods significantly in the array system with unknown mutual coupling effect.

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Mutual Coupling in Phased Arrays: A Review

International Journal of Antennas and Propagation ◽

10.1155/2013/348123 ◽

2013 ◽

Vol 2013 ◽

pp. 1-23 ◽

Cited By ~ 47

Author(s):

Hema Singh ◽

H. L. Sneha ◽

R. M. Jha

Keyword(s):

Mutual Coupling ◽

Phased Arrays ◽

Coupling Effect ◽

Doa Estimation ◽

Interference Rejection ◽

Radiation Characteristics ◽

Resolution Capability ◽

Different Types ◽

Signal Environment ◽

Array Performance

The mutual coupling between antenna elements affects the antenna parameters like terminal impedances, reflection coefficients and hence the antenna array performance in terms of radiation characteristics, output signal-to-interference noise ratio (SINR), and radar cross section (RCS). This coupling effect is also known to directly or indirectly influence the steady state and transient response, the resolution capability, interference rejection, and direction-of-arrival (DOA) estimation competence of the array. Researchers have proposed several techniques and designs for optimal performance of phased array in a given signal environment, counteracting the coupling effect. This paper presents a comprehensive review of the methods that model and mitigate the mutual coupling effect for different types of arrays. The parameters that get affected due to the presence of coupling thereby degrading the array performance are discussed. The techniques for optimization of the antenna characteristics in the presence of coupling are also included.

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The Research of DOA Estimation Algorithms in the Conformal Array Antenna

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.743.471 ◽

2015 ◽

Vol 743 ◽

pp. 471-473

Author(s):

C.Z. Sun

Keyword(s):

Doa Estimation ◽

Array Antenna ◽

Signal Subspace ◽

Music Algorithm ◽

Estimation Algorithms ◽

Conformal Array ◽

Array Antennas ◽

Peak Search ◽

Simulation Results ◽

Rayleigh Limit

To the conformal array antennas, the conventional DOA estimation algorithms will be affected by the Rayleigh limit. While, the MUSIC algorithm can solve this problem, it fully utilizes the orthogonality of noise subspace and signal subspace. It can achieve the DOA estimation through the spectrum peak search. The MUSIC algorithm is analyzed. Based on the cylindrical and conical array antenna, the algorithms are simulated. The simulation results show that the array arrangement mode can exert an important influence on the DOA estimation.

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Cumulant-Based DOA Estimation of Noncircular Signals against Unknown Mutual Coupling

Sensors ◽

10.3390/s20030878 ◽

2020 ◽

Vol 20 (3) ◽

pp. 878

Author(s):

Baoping Wang ◽

Junhao Zheng

Keyword(s):

Degrees Of Freedom ◽

Mutual Coupling ◽

Doa Estimation ◽

Coherent Signals ◽

Rank Reduction ◽

Communication Signals ◽

Effective Aperture ◽

Virtual Array ◽

High Order Statistics ◽

High Degree

To effectively find the direction of non-circular signals received by a uniform linear array (ULA) in the presence of non-negligible perturbations between array elements, i.e., mutual coupling, in colored noise, a direction of arrival (DOA) estimation approach in the context of high order statistics is proposed in this correspondence. Exploiting the non-circularity hidden behind a certain class of wireless communication signals to build up an augmented cumulant matrix, and carrying out a reformulation of the distorted steering vector to extract the angular information from the unknown mutual coupling, by exploiting the characteristic of mutual coupling, i.e., a limited operating range and an inverse relation of coupling effects to interspace, we develop a MUSIC-like estimator based on the rank-reduction (RARE) technique to directly determine directions of incident signals without mutual coupling compensation. Besides, we provide a solution to the problem of coherency between signals and mutual coupling between sensors co-existing, by selecting a middle sub-array to mitigate the undesirable effects and exploiting the rotation-invariant property to blindly separate the coherent signals into different groups to enhance the degrees of freedom. Compared with the existing robust DOA methods to the unknown mutual coupling under the framework of fourth-order cumulants (FOC), our work takes advantage of the larger virtual array and is able to resolve more signals due to greater degrees of freedom. Additionally, as the effective aperture is virtually extended, the developed estimator can achieve better performance under scenarios with high degree of mutual coupling between two sensors. Simulation results demonstrate the validity and efficiency of the proposed method.

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