scholarly journals DOA Estimation for Mixed Uncorrelated and Coherent Sources in Multipath Environment

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Heping Shi ◽  
Wen Leng ◽  
Anguo Wang ◽  
Tongfeng Guo
Keyword(s):  
Linear Array ◽  
Estimation Method ◽  
Doa Estimation ◽  
Spatial Smoothing ◽  
Uniform Linear Array ◽  
Performance Simulation ◽  
Coherent Sources ◽  
Multipath Environment ◽  
Simulation Results ◽  
Effectiveness And Efficiency

A novel direction-of-arrival (DOA) estimation method is proposed to cope with the scenario where a number of uncorrelated and coherent narrowband sources simultaneously impinge on the far-field of a uniform linear array (ULA). In the proposed method, the DOAs of uncorrelated sources are firstly estimated by utilizing the property of the moduli of eigenvalues of the DOA matrix. Afterwards, the contributions of uncorrelated sources and the interference of noise are eliminated completely by exploiting the improved spatial differencing technique and only the coherent components remain in the spatial differencing matrix. Finally, the remaining coherent sources can be resolved by performing the improved spatial smoothing scheme on the spatial differencing matrix. The presented method can resolve more number of sources than that of the array elements and distinguish the uncorrelated and coherent sources that come from the same direction as well as improving the estimation performance. Simulation results demonstrate the effectiveness and efficiency of the proposed method.

scholarly journals Compressed Sensing-Based DOA Estimation with Unknown Mutual Coupling Effect

Electronics ◽  
2018 ◽  
Vol 7 (12) ◽  
pp. 424 ◽  
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.

USTC-MUSIC Algorithm for DOA Estimation of Coherent Sources Using Single Vector Hydrophone

2014 ◽  
Vol 530-531 ◽  
pp. 530-533
Author(s):  
Jin Fang Cheng ◽  
Chao Ran Zhang ◽  
Wei Zhang
Keyword(s):  
Correlation Matrix ◽  
Temporal Correlation ◽  
Doa Estimation ◽  
Spatial Smoothing ◽  
Music Algorithm ◽  
Correlation Matrices ◽  
Vector Hydrophone ◽  
Coherent Sources ◽  
Simulation Results ◽  
Spatio Temporal

The MUSIC algorithm cannot deal with the problem of DOA estimation of coherent sources, this paper proposes the USTC (unitary spatio-temporal correlation matrices)-MUSIC algorithm using single vector hydrophone to solve this problem, by utilizing the unitary spatio-temporal correlation matrix instead of the covariance matrix. The simulation results demonstrate that the USTC-MUSIC algorithm has a better ability to distinguish the coherent sources from different directions than the spatial smoothing MUSIC algorithm.

Peak‐to‐peak search: fast and accurate DOA estimation method for arbitrary non‐uniform linear array

2015 ◽  
Vol 51 (25) ◽  
pp. 2078-2080 ◽  
Author(s):  
Li Wei ◽  
Wei Shao ◽  
Wangdong Qi ◽  
Jianhua Chen
Keyword(s):  
Linear Array ◽  
Estimation Method ◽  
Doa Estimation ◽  
Uniform Linear Array ◽  
Peak Search

scholarly journals Off-Grid DoA Estimation on Non-Uniform Linear Array Using Constrained Hermitian Matrix

Energies ◽  
2020 ◽  
Vol 13 (21) ◽  
pp. 5775
Author(s):  
Hyeonjin Chung ◽  
Jeungmin Joo ◽  
Sunwoo Kim
Keyword(s):  
Toeplitz Matrix ◽  
Linear Array ◽  
Hermitian Matrix ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Estimation Accuracy ◽  
Uniform Linear Array ◽  
Atomic Norm ◽  
Array Structures ◽  
Simulation Results

In this paper, an off-grid direction-of-arrival (DoA) estimation algorithm which can work on a non-uniform linear array (NULA) is proposed. The original semidefinite programming (SDP) representation of the atomic norm exploits a summation of one-rank matrices constructed by atoms, where the summation of one-rank matrices equals a Hermitian Toeplitz matrix when using the uniform linear array (ULA). On the other hand, when the antennas in the array are placed arbitrarily, the summation of one-rank matrices is a Hermitian matrix whose diagonal elements are equivalent. Motivated by this property, the proposed algorithm replaces the Hermitian Toeplitz matrix in the original SDP with the constrained Hermitian matrix. Additionally, when the antennas are placed symmetrically, the performance can be enforced by adding extra constraints to the Hermitian matrix. The simulation results show that the proposed algorithm achieves higher estimation accuracy and resolution than other algorithms on both array structures; i.e., the arbitrary array and the symmetric array.

scholarly journals Two-Dimensional DOA Estimation in Compressed Sensing with Compressive-Reduced Dimension-lp-MUSIC

2015 ◽  
Vol 2015 ◽  
pp. 1-9
Author(s):  
Weijian Si ◽  
Xinggen Qu ◽  
Lutao Liu ◽  
Zhiyu Qu
Keyword(s):  
Compressed Sensing ◽  
Estimation Method ◽  
Doa Estimation ◽  
Superior Performance ◽  
Two Dimensional ◽  
Improve Performance ◽  
Performance Simulation ◽  
Pair Matching ◽  
Reduced Dimension ◽  
Simulation Results

This paper presents a novel two-dimensional (2D) direction of arrival (DOA) estimation method in compressed sensing (CS) to remove the estimation failure problem and achieve superior performance. The proposed method separates the steering vector into two parts to construct two corresponding noise subspaces by introducing electric angles. Then, electric angles are estimated based on the constructed noise subspaces. In order to estimate the azimuth and elevation angles in terms of estimates of electric angles, arc-tangent operations are exploited. The arc-tangent is a one-to-one function and allows the value of the argument to be larger than unity so that the proposed method never fails. The proposed method can avoid pair matching to reduce the computational complexity and extend the number of snapshots to improve performance. Simulation results show that the proposed method can avoid estimation failure occurrence and has superior performance as compared to existing methods.

DOA Estimation of Noncircular Signals for Coprime Linear Array via Polynomial Root-Finding Technique

2020 ◽  
pp. 2150028
Author(s):  
Hui Zhai ◽  
Zheng Li ◽  
Xiaofei Zhang
Keyword(s):  
Linear Array ◽  
Doa Estimation ◽  
Music Algorithm ◽  
Uniform Linear Array ◽  
Estimation Algorithms ◽  
Root Finding ◽  
Noncircular Signals ◽  
Peak Search ◽  
Simulation Results ◽  
Polynomial Root Finding

In this paper, we investigate the direction of arrival (DOA) estimation problem of noncircular signals for coprime linear array (CLA). From the perspective of the CLA as extracted from a filled uniform linear array (ULA), a noncircular root-MUSIC algorithm is proposed to estimate the DOA which can avoid the spectral peak search and lower the computational complexity. Due to the noncircular characteristic, the proposed algorithm enables to resolve more sources than sensors. Meanwhile, the proposed algorithm has better angle estimation performance than some conventional DOA estimation algorithms. Numerical simulation results illustrate the performance of the proposed method.

scholarly journals Sparse Cumulants Fitting for Direction-of-Arrival Estimation without Redundancy

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Shuang Li ◽  
Xiaoxiao Jiang ◽  
Sai Ma ◽  
Yingguan Wang
Keyword(s):  
Gaussian Noise ◽  
Software Package ◽  
A Priori ◽  
Estimation Method ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Direction Of Arrival Estimation ◽  
Simulation Results ◽  
Effectiveness And Efficiency ◽  
Array Output

A novel direction-of-arrival (DOA) estimation method is proposed based on the sparse cumulants fitting without redundancy. Firstly, we derive that some fourth order cumulants of the array output are redundant and therefore are removed to reduce computational complexity. Then, the left cumulants are sparsely represented on an overcomplete basis and the DOAs are resolved by using a software package. Despite introducing a high variance, the proposed method shows several advantages including the ability to detect more sources than sensors, high resolution, and robustness to all kinds of Gaussian noise. Besides, our method does not have to know, a priori, the number of sources. Simulation results are presented to illustrate the effectiveness and efficiency of the proposed method.

Wideband DOA Estimation Method Based on Khatri-Rao Subspace with Uniform Focusing

2014 ◽  
Vol 687-691 ◽  
pp. 4064-4067
Author(s):  
Jin Zhang ◽  
Shi You Qi ◽  
Ai Xia Yong
Keyword(s):  
Theoretical Analysis ◽  
Estimation Method ◽  
Doa Estimation ◽  
Computation Complexity ◽  
Simulation Results ◽  
Effectiveness And Efficiency

A new wideband DOA estimation method based on Khatri-Rao subspace using uniform focusing is presented in this paper. Due to using the uniform focusing matrix which does not require pre-estimating the DOAs of signals in advance, its resolution is improved obviously and its computation complexity is reduced greatly. Meanwhile, it can also resolve more signals than the number of array sensors. Theoretical analysis and simulation results demonstrate the effectiveness and efficiency of the method.

scholarly journals A Fourth-Order Cumulants Orthonormal Propagator Rooting Method Based on Toeplitz Approximation

2020 ◽  
Author(s):  
Heping Shi ◽  
Ning Ma ◽  
Zhiwei Guan ◽  
Lizhu Zhang ◽  
Shan Jiang
Keyword(s):  
Computational Complexity ◽  
Theoretical Analysis ◽  
Fourth Order ◽  
Linear Array ◽  
Doa Estimation ◽  
Redundant Information ◽  
Uniform Linear Array ◽  
Color Noise ◽  
Reduced Dimension ◽  
Simulation Results

Abstract A novel Toeplitz fourth-order cumulants (\operatorname{FOC} ) orthonormal propagator rooting method {\text{(TFOC-OPRM)}} to direction-of-arrival (DOA) estimation for uniform linear array (ULA) is addressed in this paper. Specifically, the modified (reduced-dimension) FOC{\kern 1pt} {\kern 1pt} (MFOC) matrix is achieved at first via removing the redundant information encompassed in the primary FOC matrix, and then the TFOC matrix which possesses Toepltiz structure can be recovered by utilizing the Toepltiz approximation method. To reduce computational complexity, we adopt an effective method which depends on the polynomial rooting technology. Finally, the DOAs of incident signals can be estimated by exploiting orthonormal propagator rooting method. The theoretical analysis coupled with simulation results show that the proposed resultant algorithm can reduce computational complexity significantly, as well as improve the estimation performance in both spatially-white noise and spatially-color noise environments.

Comparison between DOA Estimation Subspace methods for incoherent and coherent signals

2015 ◽  
Vol 1 ◽  
pp. 18
Author(s):  
Ahmed Abdalla ◽  
Suhad Mohammed ◽  
Tang Bin ◽  
Jumma Mary Atieno ◽  
Abdelazeim Abdalla
Keyword(s):  
Linear Array ◽  
Doa Estimation ◽  
Far Field ◽  
Matlab Simulation ◽  
Subspace Methods ◽  
Coherent Signals ◽  
Uniform Linear Array ◽  
Pros And Cons ◽  
Basic Concepts ◽  
And Performance

This paper considers the problem of estimating the direction of arrival (DOA) for the both incoherent and coherent signals from narrowband sources, located in the far field in the case of uniform linear array sensors. Three different methods are analyzed. Specifically, these methods are Music, Root-Music and ESPRIT. The pros and cons of these methods are identified and compared in light of different viewpoints. The performance of the three methods is evaluated, analytically, when possible, and by Matlab simulation. This paper can be a roadmap for beginners in understanding the basic concepts of DOA estimation issues, properties and performance.

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