DOA Estimation of Coherent Signals Using one Snapshot

2010 ◽  
Vol 32 (3) ◽  
pp. 604-608 ◽  
Author(s):  
Xin Xie ◽  
Guo-lin Li ◽  
Hua-wen Liu
Keyword(s):  
Doa Estimation ◽  
Coherent Signals

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.

Fuzzy System for DOA Estimation of Coherent Signals

2013 ◽  
Vol 427-429 ◽  
pp. 575-581
Author(s):  
Ya Ling Chen ◽  
Chien Chou Lin
Keyword(s):  
Fuzzy System ◽  
High Performance ◽  
Expert Knowledge ◽  
Doa Estimation ◽  
Coherent Signals ◽  
Fuzzy Logic Systems ◽  
Significant Performance ◽  
And Performance ◽  
Low Sensitivity ◽  
Resolution Estimation

This paper presents an efficient direction-of-arrival (DOA) Estimator for dealing with coherent signals. The empirical results show that significant performance degradation occurs when coherent signals coexist. Therefore, an utilizes the low sensitivity of Bartlett algorithm in estimation of DOAs for coherent signals to yield a low-resolution estimation of DOAs as initial search angle and uses fuzzy logic systems with incorporating expert knowledge to improve the resolution and performance of estimation of DOAs in coherent signals environment. Finally, numerical example was analyzed to illustrate high performance of the proposed method and to confirm the designed procedure.

2D DOA Estimation Using Sparse Representation of Higher-Order Power of Covariance Matrix

2014 ◽  
Vol 998-999 ◽  
pp. 779-783
Author(s):  
Zheng Luo ◽  
Fei Yu ◽  
Lin Wu ◽  
Yuan Liu
Keyword(s):  
Covariance Matrix ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Higher Order ◽  
Eigenvalue Decomposition ◽  
Coherent Signals ◽  
Sparse Decomposition ◽  
Sparse Signal Representation ◽  
2D Doa Estimation ◽  
Source Signals

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.

Two-stage DOA estimation of independent and coherent signals in spatially coloured noise

2016 ◽  
Vol 128 ◽  
pp. 350-359 ◽  
Author(s):  
Yuexian Wang ◽  
Matthew Trinkle ◽  
Brian W.-H. Ng
Keyword(s):  
Doa Estimation ◽  
Coherent Signals ◽  
Two Stage ◽  
Coloured Noise
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