eprintid: 3571
rev_number: 7
eprint_status: archive
userid: 273
dir: disk0/00/00/35/71
datestamp: 2019-10-14 03:02:09
lastmod: 2019-10-14 03:02:09
status_changed: 2019-10-14 03:02:09
type: article
metadata_visibility: show
creators_name: Tran Cao, Quyen
creators_id: quyentc@vnu.edu.vn
title: Matched Field Processing For Source Localization Based on
An Approach of Riemannian Geometry
ispublished: pub
subjects: Communications
subjects: ECE
subjects: isi
divisions: fac_fet
abstract: The matched field processing (MFP) for source localization has long history, and remains a viable area of research as well as application of SONAR. Some methods such as empirical mode decomposition, adaptive MFP, compressive MFP and MFP using Riemannian geometry have been introduced recently in order to increase the performance of conventional MFP. In case of ocean environment variability, there are many modeled field replicas thus the number of degree of freedom is increased, consequently the true source selection becomes more complexity. In this paper, we presents a MFP using an approach of Riemannian geometry in which Riemannian distance is obtained in close-form from a new isometric mapping and 20 modeled field replicas that are received in simulation from variable sound speeds. On the basis of the proposed MFP and simulation results, the source localization could be found in a more realistic manner.
date: 2019-09
full_text_status: none
publication: AKUSTIKA
refereed: FALSE
issn: 25708775
related_url_url: https://www.journalakustika.com/journal/volume-33-en/
related_url_type: pub
citation:   Tran Cao, Quyen  (2019) Matched Field Processing For Source Localization Based on An Approach of Riemannian Geometry.  AKUSTIKA .    ISSN 25708775