AI Chat AI Image Generator AI Video Text to Speech

Multiple source direction of arrival estimation using subspace pseudointensity vectors

11/28/2018

∙

by Alastair H. Moore, et al.

∙

∙

The recently proposed subspace pseudointensity method for direction of arrival estimation is applied in the context of Tasks 1 and 2 of the LOCATA Challenge using the Eigenmike recordings. Specific implementation details are described and results reported for the development dataset, for which the ground truth source directions are available. For both single and multiple source scenarios, the average absolute error angle is about 9 degrees.

research

∙ 07/28/2020

Performance Analysis of Noise Subspace-based Narrowband Direction-of-Arrival (DOA) Estimation Algorithms on CPU and GPU

High-performance computing of array signal processing problems is a crit...

0 Hamza Eray, et al. ∙

research

∙ 07/10/2023

Exploiting an External Microphone for Binaural RTF-Vector-Based Direction of Arrival Estimation for Multiple Speakers

In hearing aid applications, an important objective is to accurately est...

0 Daniel Fejgin, et al. ∙

research

∙ 04/12/2020

Direction of Arrival Estimation for a Vector Sensor Using Deep Neural Networks

A vector sensor, a type of sensor array with six collocated antennas to ...

0 Jianyuan Yu, et al. ∙

research

∙ 01/25/2021

Using Angle of Arrival for Improving Indoor Localization

In this paper, we primarily explore the improvement of single stream aud...

0 Sai Koppula, et al. ∙

research

∙ 02/25/2022

A deep learning approach for direction of arrival estimation using automotive-grade ultrasonic sensors

In this paper, a deep learning approach is presented for direction of ar...

0 Mohamed Shawki Elamir, et al. ∙

research

∙ 06/14/2021

Multiobjective Bilevel Evolutionary Approach for Off-Grid Direction-of-Arrival Estimation

The source number identification is an essential step in direction-of-ar...

0 Bai Yan, et al. ∙

research

∙ 10/10/2019

First Order Ambisonics Domain Spatial Augmentation for DNN-based Direction of Arrival Estimation

In this paper, we propose a novel data augmentation method for training ...

0 Luca Mazzon, et al. ∙