Off-grid DOA estimation of correlated sources for nonuniform linear array through hierarchical sparse recovery in a Bayesian framework and asymptotic minimum variance criterion

This paper presents a signal direction-of-arrival (DOA) estimation approach that possesses excellent performance in spatial and temporal correlated signals environments. Firstly, an algebraic solution of the null subspace is derived based on the Vandermonde structured steering vectors of uniform linear array when all the sources possess identical nonzero mean value, and then, the DOA estimation is obtained with a polynomial rooting method. The novel algorithm performs much better than the conventional algorithms in the situation that the sources are closely spaced or correlated, and simulations have verified the validity of the algorithm.

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Comparison between DOA Estimation Subspace methods for incoherent and coherent signals

Journal of Communications Technology Electronics and Computer Science ◽

10.22385/jctecs.v1i0.13 ◽

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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A Formulation of 1-D Search Technique for 2-D DOA Estimation Using Orthogonally Polarized Components of Linear Array

IEEE Antennas and Wireless Propagation Letters ◽

10.1109/lawp.2015.2395072 ◽

2015 ◽

Vol 14 ◽

pp. 1117-1120 ◽

Cited By ~ 8

Author(s):

B. R. Karthikeyan ◽

Govind R. Kadambi ◽

Yuri A. Vershinin

Keyword(s):

Linear Array ◽

Doa Estimation ◽

Search Technique

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Weighted measurement fusion Kalman filter based on linear unbiased minimum variance criterion

Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference ◽

10.1109/cdc.2009.5399691 ◽

2009 ◽

Cited By ~ 4

Author(s):

Yuan Gao ◽

Chenjian Ran ◽

Zili Deng

Keyword(s):

Kalman Filter ◽

Minimum Variance ◽

Variance Criterion

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A covariance matrix shrinkage method with Toeplitz rectified target for DOA estimation under the uniform linear array

AEU - International Journal of Electronics and Communications ◽

10.1016/j.aeue.2017.06.026 ◽

2017 ◽

Vol 81 ◽

pp. 50-55 ◽

Cited By ~ 8

Author(s):

Yanyan Liu ◽

Xiaoying Sun ◽

Shishun Zhao

Keyword(s):

Covariance Matrix ◽

Linear Array ◽

Doa Estimation ◽

Uniform Linear Array ◽

Matrix Shrinkage ◽

Shrinkage Method

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2-D DOA Estimation with Propagator Method for Correlated Sources under Unknown Symmetric Toeplitz Noise

2005 IEEE 61st Vehicular Technology Conference ◽

10.1109/vetecs.2005.1543237 ◽

2005 ◽

Author(s):

N. Tayem ◽

Hyuck M. Kwon ◽

N. Tayem ◽

Hyuck M. Kwon

Keyword(s):

Doa Estimation ◽

Correlated Sources ◽

Propagator Method

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DOA Estimation for Coprime Linear Array Based on MI-ESPRIT and Lookup Table

Sensors ◽

10.3390/s18093043 ◽

2018 ◽

Vol 18 (9) ◽

pp. 3043 ◽

Cited By ~ 6

Author(s):

Weike Zhang ◽

Xi Chen ◽

Kaibo Cui ◽

Tao Xie ◽

Naichang Yuan

Keyword(s):

Linear Array ◽

Estimation Algorithm ◽

Doa Estimation ◽

Spatial Spectrum ◽

Angle Measurement ◽

Lookup Table ◽

Signal Parameters ◽

Estimation Precision ◽

Simulation Results ◽

The Relationship

In order to improve the angle measurement performance of a coprime linear array, this paper proposes a novel direction-of-arrival (DOA) estimation algorithm for a coprime linear array based on the multiple invariance estimation of signal parameters via rotational invariance techniques (MI-ESPRIT) and a lookup table method. The proposed algorithm does not require a spatial spectrum search and uses a lookup table to solve ambiguity, which reduces the computational complexity. To fully use the subarray elements, the DOA estimation precision is higher compared with existing algorithms. Moreover, the algorithm avoids the matching error when multiple signals exist by using the relationship between the signal subspace of two subarrays. Simulation results verify the effectiveness of the proposed algorithm.

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