eprintid: 4587
rev_number: 6
eprint_status: archive
userid: 273
dir: disk0/00/00/45/87
datestamp: 2021-07-26 02:06:10
lastmod: 2021-07-26 02:06:10
status_changed: 2021-07-26 02:06:10
type: article
metadata_visibility: show
creators_name: Tran Cao, Quyen
creators_id: quyentc@vnu.edu.vn
title: Stochastic Matched Field Processing Using 
Directed Riemannian Distance
ispublished: inpress
subjects: Communications
divisions: fac_fet
abstract: The Matched Field Processing (MFP) plays a crucial role in modern passive SONAR system since its effectiveness of underwater source localization. Their applications are but not limited to floating boat localization, submarine localization, fish finding as well as ocean environmental parameters determining.   In the past, the stochastic matched field processing (SMFP) are derived on the basis of Riemannian distances (RDs) which were calculated using isometric mappings (IMs). In this paper, a new STMP is provided using directed RDs which were obtained by solving the geodesic equations directly instead of using IMs. In addition, we exploit the symmetric property of Riemannian manifold to solve the geodesic equation in the simple manner. The performance of the proposed STMP outperformed to that of standard algorithm at the expense of a little more of computation.
date: 2021-09
full_text_status: public
publication: AKUSTIKA
volume: 40
pagerange: 3-7
refereed: FALSE
issn: 25708775
citation:   Tran Cao, Quyen  (2021) Stochastic Matched Field Processing Using Directed Riemannian Distance.  AKUSTIKA, 40 .   pp. 3-7.  ISSN 25708775    (In Press)  
document_url: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/4587/1/01%20Tran%20Cao%20Quyen.pdf