Adaptive identification of sparse underwater acoustic channels with a mix of static and time-varying parameters - Publication - MOST Wiedzy

Search

Adaptive identification of sparse underwater acoustic channels with a mix of static and time-varying parameters

Abstract

We consider identification of sparse linear systems with a mix of static and time-varying parameters. Such systems are typical in underwater acoustics (UWA), for instance, in applications requiring identi- fication of the acoustic channel, such as UWA communications, navigation and continuous-wave sonar. The recently proposed fast local basis function (fLBF) algorithm provides high performance when identi- fying time-varying systems. In this paper, we further improve the performance of the fLBF algorithm by exploiting properties of the system. Specifically, we propose an adaptive time-invariance test to identify whether a particular system tap is static or time-varying and exploit this knowledge for choosing the number of basis functions. We also propose a regularization scheme that exploits the system sparsity and an adaptive technique for estimating the regularization parameter. Finally, a debiasing technique is proposed to reduce an inherent bias of fLBF estimates. The high performance of the fLBF algorithm with the proposed techniques is demonstrated in scenarios of UWA communications, using numerical and real experiments.

Citations

  • 0

    CrossRef

  • 0

    Web of Science

  • 0

    Scopus

Keywords

Details

Category:
Articles
Type:
artykuły w czasopismach
Published in:
SIGNAL PROCESSING no. 200,
ISSN: 0165-1684
Language:
English
Publication year:
2022
Bibliographic description:
Niedźwiecki M., Gańcza A., Shen L., Zakharov Y.: Adaptive identification of sparse underwater acoustic channels with a mix of static and time-varying parameters// SIGNAL PROCESSING -Vol. 200,iss. 108664 (2022),
DOI:
Digital Object Identifier (open in new tab) 10.1016/j.sigpro.2022.108664
Sources of funding:
Verified by:
Gdańsk University of Technology

seen 1 times

Recommended for you

Meta Tags