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

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
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.

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

Sensors ◽  
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.

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.

Direction of Arrival Estimation Under Near-Field Interference Using Matrix Filter

2015 ◽  
Vol 23 (04) ◽  
pp. 1540007 ◽  
Author(s):  
Guolong Liang ◽  
Wenbin Zhao ◽  
Zhan Fan
Keyword(s):  
Near Field ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Direction Of Arrival Estimation ◽  
Far Field ◽  
Data Simulation ◽  
Estimation Algorithms ◽  
Simulation Results

Direction of arrival (DOA) estimation is of great interest due to its wide applications in sonar, radar and many other areas. However, the near-field interference is always presented in the received data, which may result in degradation of DOA estimation. An approach which can suppress the near-field interference and preserve the far-field signal desired by using a spatial matrix filter is proposed in this paper and some typical DOA estimation algorithms are adjusted to match the filtered data. Simulation results show that the approach can improve capability of DOA estimation under near-field inference efficiently.

scholarly journals AR Model-Based Direction-of-Arrival Estimation of Coherent Signals in the Presence of Unknown Mutual Coupling

2013 ◽  
Vol 2013 ◽  
pp. 1-6
Author(s):  
Zhi-Chao Sha ◽  
Zhang-Meng Liu ◽  
Zhi-Tao Huang ◽  
Yi-Yu Zhou
Keyword(s):  
Mutual Coupling ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Ar Model ◽  
Estimation Accuracy ◽  
Direction Of Arrival Estimation ◽  
Coherent Signals ◽  
Model Based ◽  
Mixing Matrix ◽  
Simulation Results

This paper addresses the problem of direction-of-arrival (DOA) estimation of coherent signals in the presence of unknown mutual coupling, and an autoregression (AR) model-based method is proposed. The effects of mutual coupling can be eliminated by the inherent mechanism of the proposed algorithm, so the DOAs can be accurately estimated without any calibration sources. After the mixing matrix is estimated by independent component analysis (ICA), several parameter equations are established upon the mixing matrix. Finally, all DOAs of coherent signals are estimated by solving these equations. Compared with traditional methods, the proposed method has higher angle resolution and estimation accuracy. Simulation results demonstrate the effectiveness of the algorithm.

scholarly journals Sparsity-Based DOA Estimation with Gain and Phase Error Calibration of Generalized Nested Array

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Ziang Feng ◽  
Guoping Hu ◽  
Hao Zhou
Keyword(s):  
Degrees Of Freedom ◽  
Phase Error ◽  
Doa Estimation ◽  
Model Errors ◽  
Multiple Sources ◽  
Sparse Arrays ◽  
Estimation Algorithms ◽  
Phase Errors ◽  
Representation Method ◽  
Cramer Rao Bound

Sparse arrays, which can localize multiple sources with less physical sensors, have attracted more attention since they were proposed. However, for optimal performance of sparse arrays, it is usually assumed that the circumstances are ideal. But in practice, the performance of sparse arrays will suffer from the model errors like mutual coupling, gain and phase error, and sensor’s location error, which causes severe performance degradation or even failure of the direction of arrival (DOA) estimation algorithms. In this study, we follow with interest and propose a covariance-based sparse representation method in the presence of gain and phase errors, where a generalized nested array is employed. The proposed strategy not only enhances the degrees of freedom (DOFs) to deal with more sources but also obtains more accurate DOA estimations despite gain and phase errors. The Cramer–Rao bound (CRB) derivation is analyzed to demonstrate the robustness of the method. Finally, numerical examples illustrate the effectiveness of the proposed method from DOA estimation.

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.

The Research of DOA Estimation Algorithms in the Conformal Array Antenna

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.

scholarly journals COPRIME ARRAY PARAMETERS OPTIMIZATION FOR DOA ESTIMATION

2021 ◽  
Vol 4 (2) ◽  
pp. 23-32
Author(s):  
Fatimah A. Salman ◽  
Bayan M. Sabbar
Keyword(s):  
Mutual Coupling ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Parameters Optimization ◽  
Degree Of Freedom ◽  
Direction Of Arrival Estimation ◽  
Sparse Arrays ◽  
Sparse Array ◽  
Simulation Results ◽  
Coprime Array

Sparse array such as the coprime array is one of the most preferable sparse arrays for direction of arrival estimation due to its properties, like simplicity, capability of resolving more sources than the number of elements and resistance to mutual coupling issue.  In this paper, a new coprime array model is proposed to increase the number of degree of freedom (DOF) and improve the performance of coprime array.   The new designed array can avoid the mutual coupling by minimizing the lag redundancy and expand the central lags in the virtual difference co-array. Thus, the propose structure can resolve more sources than the prototype coprime array using the same number of elements with improved direction of arrival estimation. Simulation results demonstrate that the proposed array model is more efficient than the others coprime array model.

scholarly journals An OPMA for Robust Mutual Coupling Coefficients Estimation of URA with Single Snapshot in MIMO HF Sky-Wave Radar

2016 ◽  
Vol 2016 ◽  
pp. 1-11
Author(s):  
Yuguan Hou ◽  
Qingguo Jin ◽  
Shaochuan Wu ◽  
Zhuoming Li
Keyword(s):  
Mutual Coupling ◽  
Signal To Noise Ratio ◽  
Mean Shift ◽  
Success Probability ◽  
Doa Estimation ◽  
Coupling Coefficients ◽  
Music Algorithm ◽  
Low Snr ◽  
Wave Radar ◽  
Single Snapshot

Due to the fluctuation of the signal-to-noise ratio (SNR) and the single snapshot case in the MIMO HF sky-wave radar system, the accuracy of the online estimation of the mutual coupling coefficients matrix of the uniform rectangle array (URA) might be degraded by the classical approach, especially in the case of low SNR. In this paper, an Online Particle Mean-Shift Approach (OPMA) is proposed, which is to get a relatively more effective estimation of the mutual coupling coefficients matrix with the low SNR. Firstly, the spatial smoothing technique combined with the MUSIC algorithm of URA is introduced for the DOA estimation of the multiple targets in the case of single snapshot which are taken as coherent sources. Then, based on the idea of the particle filter, the online particles with a moderate computational complexity are used to generate some different estimation results. Finally, the mean-shift algorithm is applied to get a more robust estimate of the equivalent mutual coupling coefficients matrix. The simulation results demonstrate the validity of the proposed approach in terms of the success probability, the statistics of bias, and the variance. The proposed approach is more robust and more accurate than the other two approaches.

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