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

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.

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.


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 998-999 ◽  
pp. 779-783
Author(s):  
Zheng Luo ◽  
Fei Yu ◽  
Lin Wu ◽  
Yuan Liu

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.


2019 ◽  
Vol 2019 ◽  
pp. 1-10
Author(s):  
Wu Wei ◽  
Xu Le ◽  
Zhang Xiaofei ◽  
Li Jianfeng

In this paper, the topic of coherent two-dimensional direction of arrival (2D-DOA) estimation is investigated. Our study jointly utilizes the compressed sensing (CS) technique and the parallel profiles with linear dependencies (PARALIND) model and presents a 2D-DOA estimation algorithm for coherent sources with the uniform rectangular array. Compared to the traditional PARALIND decomposition, the proposed algorithm owns lower computational complexity and smaller data storage capacity due to the process of compression. Besides, the proposed algorithm can obtain autopaired azimuth angles and elevation angles and can achieve the same estimation performance as the traditional PARALIND, which outperforms some familiar algorithms presented for coherent sources such as the forward backward spatial smoothing-estimating signal parameters via rotational invariance techniques (FBSS-ESPRIT) and forward backward spatial smoothing-propagator method (FBSS-PM). Extensive simulations are provided to validate the effectiveness of the proposed CS-PARALIND algorithm.


2020 ◽  
Vol E103.B (3) ◽  
pp. 240-246
Author(s):  
Gengxin NING ◽  
Shenjie JIANG ◽  
Xuejin ZHAO ◽  
Cui YANG

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