scholarly journals An Improved MUSIC Algorithm for DOA Estimation of Non-Coherent Signals with Planar Array

2018 ◽  
Vol 1060 ◽  
pp. 012026
Author(s):  
Liu Yaning ◽  
Fu Juntao ◽  
Ran Xinghao ◽  
Ming Le
Keyword(s):  
Doa Estimation ◽  
Coherent Signals ◽  
Music Algorithm ◽  
Planar Array

scholarly journals Polarization and DOA Estimation Based on Dual-Polarized Conformal Array

2019 ◽  
Vol 2019 ◽  
pp. 1-9
Author(s):  
Chao Liu ◽  
Shuai Xiang ◽  
Liangfeng Xu ◽  
Zhengfei Fang
Keyword(s):  
Doa Estimation ◽  
Signal Classification ◽  
Orthogonal Polarization ◽  
Coherent Signals ◽  
Music Algorithm ◽  
Multiple Signal Classification ◽  
Polarization Signal ◽  
Conformal Array ◽  
Dual Polarized ◽  
Cramer Rao Bound

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.

DOA Estimation Algorithm in Switch Antenna Array with a Single Cycle of Sampled Data

2011 ◽  
Vol 291-294 ◽  
pp. 3250-3254 ◽  
Author(s):  
Ke Zhang ◽  
Peng Ma ◽  
Jian Yun Zhang
Keyword(s):  
Antenna Array ◽  
Toeplitz Matrix ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Eigenvalue Decomposition ◽  
The Novel ◽  
Sampled Data ◽  
Coherent Signals ◽  
Music Algorithm ◽  
Single Cycle

For DOA estimation of coherent signals in switch antenna array (SAA), a new fast algorithm is proposed. Instead of conventional sub-space algorithm’s covariance matrix, a Toeplitz matrix is constructed with a single cycle of sampled data. It is proved theoretically that the ranks of the Toeplitz matrix is equal to the number of signal sources and has no relations with the coherency of the signal source. Through eigenvalue decomposition, signal and noise subspace are obtained respectively, then DOA estimation can be done by one-dimensional spectral peak searching according to the MUSIC algorithm. The theoretical analysis and simulation results demonstrate validity and superiority of the novel algorithm.

scholarly journals Coherent Target Direction-of-Arrival Estimation for Coprime Arrays: From Spatial Smoothing Perspective

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Dongming Wu ◽  
Fangzheng Liu ◽  
Zhihui Li ◽  
Zhenzhong Han
Keyword(s):  
Direction Of Arrival ◽  
Doa Estimation ◽  
Spatial Spectrum ◽  
Spatial Smoothing ◽  
Phase Ambiguity ◽  
Coherent Signals ◽  
Music Algorithm ◽  
Multiple Signal Classification ◽  
Common Peak ◽  
Coprime Arrays

In this paper, we investigate the issue of direction-of-arrival (DOA) estimation of multiple signals in coprime arrays. An algorithm based on multiple signal classification (MUSIC) and forward and backward spatial smoothing (FBSS) is used for DOA estimation of this signal caused by multipath and interference. The large distance between adjacent elements of each subarray in the coprime arrays will bring phase ambiguity issues. According to the feature of the coprime number, the ambiguity problem can be eliminated. The correct DOA estimation can be obtained by searching for the common peak of the spatial spectrum and finding the overlapping peaks in the MUSIC spectrum of the two subarrays. For the rank deficit problem caused by the coherent signal, the FBSS algorithm is used for signal preprocessing before the MUSIC algorithm. Theoretical analysis and simulation results show that the algorithm can effectively solve the rank deficiency and phase ambiguity problems caused by coherent signals and sparse arrays in the coprime arrays.

scholarly journals Computationally Efficient Ambiguity-Free Two-Dimensional DOA Estimation Method for Coprime Planar Array: RD-Root-MUSIC Algorithm

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Luo Chen ◽  
Changbo Ye ◽  
Baobao Li
Keyword(s):  
Degrees Of Freedom ◽  
Estimation Method ◽  
Doa Estimation ◽  
Estimation Accuracy ◽  
Two Dimensional ◽  
Computationally Efficient ◽  
Music Algorithm ◽  
Estimation Algorithms ◽  
Planar Array ◽  
2D Doa Estimation

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.

Interference Localization via Direction of Arrival Estimation for Satellite with Planar Array

2014 ◽  
Vol 1049-1050 ◽  
pp. 1788-1791
Author(s):  
Xiao Feng Qiu ◽  
Xiao Fei Zhang
Keyword(s):  
Computational Cost ◽  
Estimation Method ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Music Algorithm ◽  
Angle Estimation ◽  
Multiple Signal Classification ◽  
Estimation Performance ◽  
Planar Array ◽  
Esprit Algorithm

This paper presents the model of satellite planar array, and interference localization via direction of arrival (DOA) estimation. We derive a dimension reduction DOA estimaton algorithm therein. The proposed algorithm, which only requires a one-dimensional local searching, can avoid the high computational cost within two-dimensional multiple signal classification (2D-MUSIC) algorithm. We illustrate that the proposed algorithm has better angle estimation performance than estimation method of signal parameters via rotational invariance technique (ESPRIT) algorithm, and has very close angle estimation performance to 2D-MUSIC algorithm. Furthermore, our algorithm requires no extra pairing. Simulation results present the usefulness of our algorithm.

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.

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