Deep Augmented MUSIC Algorithm for Data-Driven DoA Estimation

09/22/2021
by   Julian P. Merkofer, et al.
0

Direction of arrival (DoA) estimation is a crucial task in sensor array signal processing, giving rise to various successful model-based (MB) algorithms as well as recently developed data-driven (DD) methods. This paper introduces a new hybrid MB/DD DoA estimation architecture, based on the classical multiple signal classification (MUSIC) algorithm. Our approach augments crucial aspects of the original MUSIC structure with specifically designed neural architectures, allowing it to overcome certain limitations of the purely MB method, such as its inability to successfully localize coherent sources. The deep augmented MUSIC algorithm is shown to outperform its unaltered version with a superior resolution.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
06/04/2023

SubspaceNet: Deep Learning-Aided Subspace Methods for DoA Estimation

Direction of arrival (DoA) estimation is a fundamental task in array pro...
research
10/12/2021

An Annihilating Filter-Based DOA Estimation for Uniform Linear Array

In this paper, we propose a new method to design an annihilating filter ...
research
02/10/2019

Performance Advantages of Deep Neural Networks for Angle of Arrival Estimation

The problem of estimating the number of sources and their angles of arri...
research
09/26/2018

Bayesian inference for PCA and MUSIC algorithms with unknown number of sources

Principal component analysis (PCA) is a popular method for projecting da...
research
02/02/2022

Melody Extraction from Polyphonic Music by Deep Learning Approaches: A Review

Melody extraction is a vital music information retrieval task among musi...
research
04/23/2019

Statistical Learning and Estimation of Piano Fingering

Automatic estimation of piano fingering is important for computationally...
research
05/22/2017

StegIbiza: Steganography in Club Music Implemented in Python

This paper introduces the implementation of steganography method called ...

Please sign up or login with your details

Forgot password? Click here to reset