High‐resolution DOA estimation for cooperation networks using space‐time hopping

2016 ◽  
Vol 52 (11) ◽  
pp. 978-980 ◽  
Author(s):  
Xiangyu Li ◽  
Suxia Guo ◽  
Liang Jin ◽  
Kaizhi Huang ◽  
Lu Xia
Keyword(s):  
High Resolution ◽  
Doa Estimation ◽  
Space Time ◽  
Time Hopping

scholarly journals Reweighted ‐norm minimisation for high‐resolution DOA estimation under unknown mutual coupling

2018 ◽  
Vol 54 (23) ◽  
pp. 1346-1348 ◽  
Author(s):  
Dandan Meng ◽  
Xianpeng Wang ◽  
Mengxing Huang ◽  
Chong Shen
Keyword(s):  
High Resolution ◽  
Mutual Coupling ◽  
Doa Estimation

High-Resolution DOA Estimation Algorithm for a Single Acoustic Vector Sensor at Low SNR

2020 ◽  
Vol 68 ◽  
pp. 6142-6158
Author(s):  
Jun Zhang ◽  
Xiangyuan Xu ◽  
Zhifei Chen ◽  
Ming Bao ◽  
Xiao-Ping Zhang ◽  
...  
Keyword(s):  
High Resolution ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Acoustic Vector Sensor ◽  
Low Snr ◽  
Vector Sensor

scholarly journals Estimation of Interference Arrival Direction Based on a Novel Space-Time Conversion MUSIC Algorithm for GNSS Receivers

Sensors ◽  
2019 ◽  
Vol 19 (11) ◽  
pp. 2570 ◽  
Author(s):  
Hao Wang ◽  
Qing Chang ◽  
Yong Xu ◽  
Xianxu Li
Keyword(s):  
Doa Estimation ◽  
Space Time ◽  
Variable Step Size ◽  
Arrival Direction ◽  
Music Algorithm ◽  
Step Size ◽  
Multiple Signal Classification ◽  
Variable Step ◽  
Gnss Receivers ◽  
Interference Signals

In the estimation of the direction of arrival (DOA) for interference signals, the direction-finding error of the multiple signal classification (MUSIC) algorithm will increase in the case of multiple interferences or when the interfering signal power is weak. In this paper, a space-time conversion MUSIC (STC-MUSIC) algorithm is proposed, and the concept of a focusing parameter is introduced to improve the performance of the DOA estimation. Meanwhile, a method of variable step size peak search is proposed to reduce the amount of calculation of the STC-MUSIC algorithm. The final simulation and experimental results show that the STC-MUSIC algorithm improves the purity of the noise subspace effectively, thus improving the precision and robustness of the DOA estimation for interference signals significantly. In comparison to traditional algorithms, the convergence, stability, root mean square error (RMSE) and other performance characteristics are improved greatly.

scholarly journals Underwater Ambiguity Elimination Method Based on Co-Prime Sensor Array

Sensors ◽  
2020 ◽  
Vol 20 (21) ◽  
pp. 6058
Author(s):  
Tian Lan ◽  
Yilin Wang ◽  
Longhao Qiu
Keyword(s):  
High Resolution ◽  
Sensor Array ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Spatial Spectrum ◽  
Estimation Methods ◽  
Sensing Applications ◽  
Passive Sensing ◽  
Spatial Spectra ◽  
Beam Patterns

Recently, the direction of arrival estimation with co-prime arrays has gradually been applied in underwater scenarios because of its significant advantages over traditional uniform linear arrays. Despite the advantages of co-prime arrays, the spatial spectra obtained directly from conventional beamforming can be degraded by grating lobes due to the sparse spatial sampling in passive sensing applications, which will seriously deteriorate the estimation performance. In this paper, capon beamforming is applied to a co-prime sensor array as a pretreatment before high-resolution direction of arrival (DOA) estimation methods. The amplitudes extracted from the beam-domain outputs of two subarrays and the phases extracted from the cross-spectrum of the spatial spectrum are exploited to suppress the spurious peaks in beam patterns and eliminate ambiguities. Consequently, interference can be further mitigated, and the performance of high-resolution DOA methods will be guaranteed. Simulations show that the method proposed can improve the reliability and accuracy of DOA estimation with great value in practice.

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