Acoustic correlated sources direction finding in the presence of unknown spatial correlation noise

Authors

Abstract:

In this paper, a new method is proposed for DOA estimation of correlated acoustic signals, in the presence of unknown spatial correlation noise. By generating a matrix from the signal subspace with the Hankel-SVD method, the correlated resource information is extracted from each eigen-vector. Then a joint-diagonalization  structure is constructed of the signal subspace and basis it, independent linear component, related to sources are recovered. Simulation results and comparisons with other commonly presented methods show the capability of this algorithm in low signal-to-noise ratio and close sources.

Upgrade to premium to download articles

Sign up to access the full text

Already have an account?login

similar resources

Localization of Narrow-Band Sources in Unknown Spatially Correlated Noise

In subspace-based method for direction-of-arrival (DOA) estimation of signal wavefronts, the additive noise term is often assumed to be spatially white or known to within a multiplicative scalar. When the noise is nonwhite but has a known covariance matrix, we can still handle the problem through prewhitening. However, the problem turns to be complex when the noise field is completely unknown. ...

full text

Direction Finding in the Presence of Mutual Coupling Direction Finding in the Presence of Mutual Coupling Direction Finding in the Presence of Mutual Coupling

The area of sensor array processing has attracted considerable interest in the signal processing community. The focus of this work has been on high resolution Direction Of Arrival (DOA) estimation algorithms that detect and locate aircrafts using radar systems. These algorithms exploit the fact that an electromagnetic wave that is received by an array of antenna elements reaches each element at...

full text

Numerical study on the acoustic field of a centrifugal fan and the tonal noise sources

The widespread use of squirrel cage fans, especially in ventilation and home and industrial environments, has led to the formation of many research efforts to improve performance and reduce the sound produced by this type of fan. In the literature, the most important factor in generating sound in this category of fans is the confrontation between the rotor exit flow and the volute of the fan. I...

full text

Direction estimation in partially unknown noise fields

A fundamental assumption for most direction nding algorithms is that the background noise is uncorrelated from sensor to sensor, or known to within a multiplicative scalar. In practice this assumption is seldom ful lled, however, the spatial noise covariance may be estimated by measuring the array covariance when no signals are present. This procedure is unavoidably subjected to errors. In this...

full text

Diagnostics of noise acoustic sources

The diagnostics of the noise acoustical sources from near-field data is considered. The algorithms allowing the determination of the equivalent elementary source distribution along a radiator and the far-field reconstruction from near-field measurements are presented. Some components of the total reconstruction error are analyzed.

full text

Closed-Form Underwater Acoustic Direction-Finding with Arbitrarily Spaced Vector Hydrophones at Unknown Locations

This paper introduces a novel ESPRIT-based closedform source localization algorithm applicable to arbitrarily spaced three-dimensional arrays of vector hydrophones, whose locations need not be known. Each vector hydrophone consists of two or three identical but orthogonally oriented velocity hydrophones plus one pressure hydrophone, all spatially co-located in a point-like geometry. A velocity ...

full text

My Resources

Save resource for easier access later

Save to my library Already added to my library

{@ msg_add @}


Journal title

volume 7  issue 1

pages  1- 9

publication date 2019-09

By following a journal you will be notified via email when a new issue of this journal is published.

Keywords

No Keywords

Hosted on Doprax cloud platform doprax.com

copyright © 2015-2023