Two DOA estimation algorithms based on the theory of sparse representation

2014 ◽  
Author(s):  
Z. Luo ◽  
W. Zhao ◽  
F. Yu ◽  
Y. Liu
Keyword(s):  
Sparse Representation ◽  
Doa Estimation ◽  
Estimation Algorithms

Direction of Arrival Estimation Under Near-Field Interference Using Matrix Filter

2015 ◽  
Vol 23 (04) ◽  
pp. 1540007 ◽  
Author(s):  
Guolong Liang ◽  
Wenbin Zhao ◽  
Zhan Fan
Keyword(s):  
Near Field ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Direction Of Arrival Estimation ◽  
Far Field ◽  
Data Simulation ◽  
Estimation Algorithms ◽  
Simulation Results

Direction of arrival (DOA) estimation is of great interest due to its wide applications in sonar, radar and many other areas. However, the near-field interference is always presented in the received data, which may result in degradation of DOA estimation. An approach which can suppress the near-field interference and preserve the far-field signal desired by using a spatial matrix filter is proposed in this paper and some typical DOA estimation algorithms are adjusted to match the filtered data. Simulation results show that the approach can improve capability of DOA estimation under near-field inference efficiently.

scholarly journals Spectral Domain Sparse Representation for DOA Estimation of Signals with Large Dynamic Range

Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 5164
Author(s):  
Jacob Compaleo ◽  
Inder J. Gupta
Keyword(s):  
Sparse Representation ◽  
Antenna Array ◽  
Dynamic Range ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Single Step ◽  
Window Function ◽  
Spectral Domain ◽  
Low Sidelobe ◽  
Weighting Window

Recently, we proposed a Spectral Domain Sparse Representation (SDSR) approach for the direction-of-arrival estimation of signals incident to an antenna array. In the approach, sparse representation is applied to the conventional Bartlett spectra obtained from snapshots of the signals received by the antenna array to increase the direction-of-arrival (DOA) estimation resolution and accuracy. The conventional Bartlett spectra has limited dynamic range, meaning that one may not be able to identify the presence of weak signals in the presence of strong signals. This is because, in the conventional Bartlett spectra, uniform weighting (window) is applied to signals received by various antenna elements. Apodization can be used in the generation of Bartlett spectra to increase the dynamic range of the spectra. In Apodization, more than one window function is used to generate different portions of the spectra. In this paper, we extend the SDSR approach to include Bartlett spectra obtained with Apodization and to evaluate the performance of the extended SDSR approach. We compare its performance with a two-step SDSR approach and with an approach where Bartlett spectra is obtained using a low sidelobe window function. We show that an Apodization Bartlett-based SDSR approach leads to better performance with just single-step processing.

Enhanced covariances matrix sparse representation method for DOA estimation

2015 ◽  
Vol 51 (16) ◽  
pp. 1288-1290 ◽  
Author(s):  
Wei Cui ◽  
Tong Qian ◽  
Jing Tian
Keyword(s):  
Sparse Representation ◽  
Doa Estimation ◽  
Representation Method

scholarly journals Direction-of-Arrival Estimation of Closely Spaced Emitters Using Compact Arrays

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Hoi-Shun Lui ◽  
Hon Tat Hui
Keyword(s):  
Performance Evaluation ◽  
Matrix Pencil ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Antenna Element ◽  
Portable Devices ◽  
Estimation Algorithms ◽  
Half Wavelength ◽  
Matrix Pencil Method ◽  
Array Aperture

Performance evaluation of direction-of-arrival (DOA) estimation algorithms has continuously drawn significant attention in the past years. Most previous studies were conducted under the situation that antenna element separation is about half wavelength in order to avoid the appearance of grating lobes. On the other hand, recent developments in wireless communications have favoured the use of portable devices that utilize compact arrays with antenna element separations of less than half wavelength. Performance evaluation of DOA estimation algorithms employing compact arrays is an important and fundamental issue, but it has not been fully studied. In this paper, the performance of the matrix pencil method (MPM) that applies to DOA estimations is investigated through Monte Carlo simulations. The results show that closely spaced emitters can be accurately resolved using linear compact array with an array aperture as small as around half wavelength.

Robust Sparse Representation for DOA Estimation With Unknown Mutual Coupling Under Impulsive Noise

2020 ◽  
Vol 24 (7) ◽  
pp. 1455-1458
Author(s):  
Jiacheng Zhang ◽  
Tianshuang Qiu ◽  
Shengyang Luan
Keyword(s):  
Sparse Representation ◽  
Mutual Coupling ◽  
Impulsive Noise ◽  
Doa Estimation

scholarly journals Noniterative DOA Estimation Algorithms of Noncircular Signals in Nonuniform Noise Environment

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 188620-188627
Author(s):  
Yu Qiao ◽  
Han Wang ◽  
Xianpeng Wang ◽  
Mengxing Huang ◽  
Liangtian Wan ◽  
...  
Keyword(s):  
Doa Estimation ◽  
Noise Environment ◽  
Estimation Algorithms ◽  
Noncircular Signals
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