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

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.

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Hao Feng ◽  
Lutao Liu ◽  
Biyang Wen

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.


2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Liang-Tian Wan ◽  
Lu-Tao Liu ◽  
Wei-Jian Si ◽  
Zuo-Xi Tian

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.


2019 ◽  
Vol 2019 ◽  
pp. 1-9
Author(s):  
Chao Liu ◽  
Shuai Xiang ◽  
Liangfeng Xu ◽  
Zhengfei Fang

A dual-polarized multiple signal classification (DP-MUSIC) algorithm is presented to estimate the arrival directions and polarizations for a dual-polarized conformal array. Each polarization signal is decomposed into two orthogonal polarization components, which are considered to be a pair of coherent signals coming from the same direction but different polarization. The polarization parameters are modeled as the equivalent coherence coefficients of the orthogonal polarization components. Then, the method of decoherence can be used to decouple the information of polarization states and signal angles. After that, the direction of arrival (DOA) and polarization parameters can be estimated by the DP-MUSIC algorithm. Moreover, the angles of incident direction are re-estimated, which greatly improves the accuracy of DOA estimation. The Cramer–Rao bound (CRB) is derived and the effectiveness of the proposed algorithm is verified by Monte Carlo simulations.


2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Ziang Feng ◽  
Guoping Hu ◽  
Hao Zhou

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.


2015 ◽  
Vol 743 ◽  
pp. 471-473
Author(s):  
C.Z. Sun

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.


2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Minjie Wu ◽  
Xiaofa Zhang ◽  
Jingjian Huang ◽  
Naichang Yuan

Due to the variable curvature of the conformal carrier, the pattern of each element has a different direction. The traditional method of analyzing the conformal array is to use the Euler rotation angle and its matrix representation. However, it is computationally demanding especially for irregular array structures. In this paper, we present a novel algorithm by combining the geometric algebra with Multiple Signal Classification (MUSIC), termed as GA-MUSIC, to solve the direction of arrival (DOA) for cylindrical conformal array. And on this basis, we derive the pattern and array manifold. Compared with the existing algorithms, our proposed one avoids the cumbersome matrix transformations and largely decreases the computational complexity. The simulation results verify the effectiveness of the proposed method.


2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Chao Liu ◽  
Shunian Yin

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.


2017 ◽  
Vol 2017 ◽  
pp. 1-12
Author(s):  
Nizar Tayem ◽  
Khaqan Majeed ◽  
Ahmed A. Hussain

Two-dimensional (2D) Direction-of-Arrivals (DOA) estimation for elevation and azimuth angles assuming noncoherent, mixture of coherent and noncoherent, and coherent sources using extended three parallel uniform linear arrays (ULAs) is proposed. Most of the existing schemes have drawbacks in estimating 2D DOA for multiple narrowband incident sources as follows: use of large number of snapshots, estimation failure problem for elevation and azimuth angles in the range of typical mobile communication, and estimation of coherent sources. Moreover, the DOA estimation for multiple sources requires complex pair-matching methods. The algorithm proposed in this paper is based on first-order data matrix to overcome these problems. The main contributions of the proposed method are as follows: (1) it avoids estimation failure problem using a new antenna configuration and estimates elevation and azimuth angles for coherent sources; (2) it reduces the estimation complexity by constructing Toeplitz data matrices, which are based on a single or few snapshots; (3) it derives parallel factor (PARAFAC) model to avoid pair-matching problems between multiple sources. Simulation results demonstrate the effectiveness of the proposed algorithm.


2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Luo Chen ◽  
Changbo Ye ◽  
Baobao Li

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. Different from the conventional 2D DOA estimation algorithms based on subarray decomposition, we exploit the received data of the two subarrays jointly by mapping CPA to the full array of the CPA (FCPA), which contributes to the enhanced degrees of freedom (DOFs) and improved estimation performance. In addition, due to the ambiguity-free characteristic of the FCPA, the extra ambiguity elimination operation can be avoided. Furthermore, we convert the 2D spectral search process into 1D polynomial rooting via reduced-dimension transformation, which substantially reduces the computational complexity while preserving the estimation accuracy. Finally, numerical simulations demonstrate the superiority of the proposed algorithm.


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