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A robust method for linear array is proposed to address the difficulty of direction-of-arrival (DOA) estimation in reverberant and noisy environments. A direct-path dominance test based on the onset detection is utilized to extract…

音频与语音处理 · 电气工程与系统科学 2019-04-16 Hao Wang , Jing Lu

We present a MUSIC-based Direction of Arrival (DOA) estimation strategy using small antenna arrays, via employing deep learning for reconstructing the signals of a virtual large antenna array. Not only does the proposed strategy deliver…

信号处理 · 电气工程与系统科学 2021-03-08 Aya Mostafa Ahmed , Udaya Sampath K. P. Miriya Thanthrige , Aly El Gamal , Aydin Sezgin

We consider the problem of direction-of-arrival (DOA) estimation in unknown partially correlated noise environments where the noise covariance matrix is sparse. A sparse noise covariance matrix is a common model for a sparse array of…

Estimating the directions of arrival (DOAs) of multiple sources from a single snapshot obtained by a coherent antenna array is a well-known problem, which can be addressed by sparse signal reconstruction methods, where the DOAs are…

信号处理 · 电气工程与系统科学 2021-02-02 Tom Tirer , Oded Bialer

An analysis of the relationship between the bandwidth of acoustic signals and the required resolution of steered-response power phase transform (SRP-PHAT) maps used for sound source localization is presented. This relationship does not rely…

This article discusses the application of single vector hydrophones in the field of underwater acoustic signal processing for Direction Of Arrival (DOA) estimation. Addressing the limitations of traditional DOA estimation methods in…

声音 · 计算机科学 2025-12-29 Jiabin Guo

As massive multiple-input multiple-output (MIMO) becomes popular, direction of arrival (DOA) measurement has been made a real renaissance due to the high-resolution achieved. Thus, there is no doubt about DOA estimation using massive MIMO.…

信息论 · 计算机科学 2023-07-18 Jiangzhou Wang , Baihua Shi , Feng Shu , Qi Zhang , Di Wu , Qijuan Jie , Zhihong Zhuang , Siling Feng , Yijin Zhang

Standard Direction of Arrival (DOA) estimation methods are typically derived based on the Gaussian noise assumption, making them highly sensitive to outliers. Therefore, in the presence of impulsive noise, the performance of these methods…

机器学习 · 计算机科学 2024-05-28 Y. Li , W. Xiao , L. Zhao , Z. Huang , Q. Li , L. Li , R. C. de Lamare

Direction of arrival (DOA) estimation is a fundamental problem in array signal processing with applications spanning radar, sonar, wireless communications, and acoustic signal processing. This tutorial survey provides a comprehensive…

信号处理 · 电气工程与系统科学 2025-09-03 Amgad A. Salama

A method for estimation of direct-to-reverberant ratio (DRR) using a microphone array is proposed. The proposed method estimates the power spectral density (PSD) of the direct sound and the reverberation using the algorithm \textit{PSD…

声音 · 计算机科学 2015-11-02 Yusuke Hioka , Kenta Niwa

In this paper, we address the problem of direction of arrival (DOA) estimation for multiple targets in the presence of sensor failures in a sparse array. Generally, sparse arrays are known with very high-resolution capabilities, where N…

机器学习 · 计算机科学 2023-06-22 Aya Mostafa Ahmed , Udaya S. K. P. Miriya Thanthrige , Aydin Sezgin , Fulvio Gini

Deep learning-based direction-of-arrival (DoA) estimation has gained increasing popularity. A popular family of DoA estimation algorithms is beamforming methods, which operate by constructing a spatial filter that is applied to array…

计算工程、金融与科学 · 计算机科学 2025-12-25 Xuyao Deng , Yong Dou , Kele Xu

In this paper we present a new robust sound source localization and tracking method using an array of eight microphones (US patent pending) . The method uses a steered beamformer based on the reliability-weighted phase transform (RWPHAT)…

机器人学 · 计算机科学 2016-04-07 Jean-Marc Valin , François Michaud , Jean Rouat

Inspection robots are widely used in the field of smart grid monitoring in substations, and partial discharge (PD) is an important sign of the insulation state of equipments. PD direction of arrival (DOA) algorithms using conventional…

信号处理 · 电气工程与系统科学 2022-04-20 Wencong Xu , Yandong Li , Bingshu Chen , Yue Hu , Jianxu Li , Zijing Zeng

Multiple-input multiple-output (MIMO) systems play an essential role in direction-of-arrival (DOA) estimation. A large number of antennas used in a MIMO system imposes a huge complexity burden on the popular DOA estimation algorithms, such…

信号处理 · 电气工程与系统科学 2023-03-16 Md Imrul Hasan , Mohammad Saquib

The calibration of modern radio interferometers is a significant challenge, specifically at low frequencies. In this perspective, we propose a novel iterative calibration algorithm, which employs the popular sparse representation framework,…

天体物理仪器与方法 · 物理学 2016-06-06 Martin Brossard , Mohamed Nabil El Korso , Marius Pesavento , Rémy Boyer , Pascal Larzabal

We consider the problem of estimating the direction of arrival of desired acoustic sources in the presence of multiple acoustic interference sources. All the sources are located in noisy and reverberant environments and are received by a…

信号处理 · 电气工程与系统科学 2024-04-16 Amitay Bar , Ronen Talmon

The direction of arrival (DOA) estimation problem is addressed in this letter. A reconfigurable intelligent surface (RIS) aided system for the DOA estimation is proposed. Unlike traditional DOA estimation systems, a low-cost system with…

信号处理 · 电气工程与系统科学 2022-03-22 Peng Chen , Zihan Yang , Zhimin Chen , Ziyu Guo

Conventional direction of arrival (DOA) estimation algorithms suffer from performance degradation due to antenna pattern distortion and substantial computational complexity in real-time execution. The support vector regression (SVR)…

信号处理 · 电气工程与系统科学 2021-10-20 Md Imrul Hasan , Mohammad Saquib

This paper proposes design techniques for partially-calibrated sparse linear subarrays and algorithms to perform direction-of-arrival (DOA) estimation. First, we introduce array architectures that incorporate two distinct array categories,…

信号处理 · 电气工程与系统科学 2024-09-04 W. Leite , R. C. de Lamare , Y. Zakharov , W. Liu , M. Haardt