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High-resolution Direction-of-Arrival estimation
2022Direction of Arrival (DOA) estimation is considered one of the most crucial problems in array signal processing, with considerable research efforts for developing efficient and effective direction-finding algorithms, especially in the transportation industry, where the demand for an effective, real-time, and accurate DOA algorithm is increasing ...
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Uncertainty quantification for direction-of-arrival estimation with conformal prediction.
Journal of the Acoustical Society of America, 2023Uncertainty quantification (UQ) of deep learning (DL)-based acoustic estimation methods is useful for establishing confidence in the predictions. This is crucial to enable the real-world applicability of DL-based systems for acoustic tasks. Specifically,
Ishan D. Khurjekar, P. Gerstoft
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Mirrored Arrays for Direction-of-Arrival Estimation
ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020A mirrored array configuration, which consists of an ordinary linear array and a reflector, is proposed. The mirrored arrays can provide composable degrees of freedom (DOF) for array processing by combined measurements with the help of mechanical adjustment (e.g., movement or rotation).
Dong Zhu, Gang Li, Xiao-Ping Zhang
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Journal of the Acoustical Society of America, 2023
This paper points out a critical issue in the study of estimating the azimuth of ground sources by using the polarization characteristics of Rayleigh waves: even if the signal quality is good, the degree of polarization of Rayleigh waves varies across ...
Xin Wang +6 more
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This paper points out a critical issue in the study of estimating the azimuth of ground sources by using the polarization characteristics of Rayleigh waves: even if the signal quality is good, the degree of polarization of Rayleigh waves varies across ...
Xin Wang +6 more
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Dual Class Token Vision Transformer for Direction of Arrival Estimation in Low SNR
IEEE Signal Processing LettersIn this letter, we propose a deep learning-based method for the direction of arrival (DOA) estimation in the low signal-to-noise ratio (SNR) scenario.
Yu Guo, Zhi Zhang, Yuzhen Huang
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Deep Convolutional Network-Assisted Multiple Direction-of-Arrival Estimation
IEEE Signal Processing LettersMultiple direction-of-arrival estimation is one of the core functions in array signal processing and has many engineering applications. It is proposed that it can be realized using a two-stage strategy which consists of multiclass classification for ...
Jie Ma +3 more
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Direction of Arrival Filters for Improved Aberration Estimation
Ultrasonic Imaging, 2008Successful adaptive imaging requires accurate measurements of the aberration profile across the array surface. Two-dimensional spatial filters are used to obtain more accurate estimates of aberrating layers by suppressing wavefronts emanating from off-axis scatterers.
Jeremy J, Dahl, Thomas J, Feehan
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Subspace estimators of direction of arrival
Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers, 2004., 2005We consider in this paper a class of techniques for the estimation of the direction of arrival of a narrowband signal. Eigenvectors of a spectral covariance matrix corresponding to a number of the lowest eigenvalues are used to estimate the bearing. It is shown that the estimator has a non-standard asymptotic distribution.
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One-Bit Cramér–Rao Bound of Direction of Arrival Estimation for Deterministic Signals
IEEE Transactions on Circuits and Systems - II - Express BriefsOne-bit direction of arrival (DOA) estimation has received considerable attention in recent years due to its ability to reduce complexity, cost, and storage in radar and wireless communication systems.
Mingyang Chen +4 more
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Decentralized Direction of Arrival Estimation
2017Direction-of-arrival (DOA) estimation using partly calibrated arrays composed of multiple subarrays is employed in various practical applications, such as radar, sonar, and seismic exploration. The state-of-the-art DOA estimation algorithms require the measurements of all sensors to be available at a processing center (PC).
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