Topographic visual analytics of multibeam dynamic SONAR data

Iain Rice; David Lowe

doi:10.1109/SSPD.2014.6943326

Topographic visual analytics of multibeam dynamic SONAR data

Iain Rice
, David Lowe

Computer Science Research Group

Research output: Chapter in Book/Published conference output › Conference publication

1 Citation (Scopus)

97 Downloads (Pure)

Abstract

This paper considers the problem of low-dimensional visualisation of very high dimensional information sources for the purpose of situation awareness in the maritime environment. In response to the requirement for human decision support aids to reduce information overload (and specifically, data amenable to inter-point relative similarity measures) appropriate to the below-water maritime domain, we are investigating a preliminary prototype topographic visualisation model. The focus of the current paper is on the mathematical problem of exploiting a relative dissimilarity representation of signals in a visual informatics mapping model, driven by real-world sonar systems. A realistic noise model is explored and incorporated into non-linear and topographic visualisation algorithms building on the approach of [9]. Concepts are illustrated using a real world dataset of 32 hydrophones monitoring a shallow-water environment in which targets are present and dynamic.

Original language	English
Title of host publication	2014 Sensor Signal Processing for Defence (SSPD)
Place of Publication	Piscataway, NJ (US)
Publisher	IEEE
Number of pages	5
ISBN (Electronic)	978-1-4799-5293-9
ISBN (Print)	978-1-4799-5294-6
DOIs	https://doi.org/10.1109/SSPD.2014.6943326
Publication status	Published - 2014
Event	4th conference of the Sensor Signal Processing for Defence - Edinburgh, United Kingdom Duration: 8 Sept 2014 → 9 Sept 2014

Conference

Conference	4th conference of the Sensor Signal Processing for Defence
Abbreviated title	SSPD 2014
Country/Territory	United Kingdom
City	Edinburgh
Period	8/09/14 → 9/09/14

Bibliographical note

© 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

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10.1109/SSPD.2014.6943326

Topographic visual analytics of multibeam dynamic SONAR data
© 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Accepted author manuscript, 1.54 MB

http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6943326

Cite this

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title = "Topographic visual analytics of multibeam dynamic SONAR data",

abstract = "This paper considers the problem of low-dimensional visualisation of very high dimensional information sources for the purpose of situation awareness in the maritime environment. In response to the requirement for human decision support aids to reduce information overload (and specifically, data amenable to inter-point relative similarity measures) appropriate to the below-water maritime domain, we are investigating a preliminary prototype topographic visualisation model. The focus of the current paper is on the mathematical problem of exploiting a relative dissimilarity representation of signals in a visual informatics mapping model, driven by real-world sonar systems. A realistic noise model is explored and incorporated into non-linear and topographic visualisation algorithms building on the approach of [9]. Concepts are illustrated using a real world dataset of 32 hydrophones monitoring a shallow-water environment in which targets are present and dynamic.",

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AB - This paper considers the problem of low-dimensional visualisation of very high dimensional information sources for the purpose of situation awareness in the maritime environment. In response to the requirement for human decision support aids to reduce information overload (and specifically, data amenable to inter-point relative similarity measures) appropriate to the below-water maritime domain, we are investigating a preliminary prototype topographic visualisation model. The focus of the current paper is on the mathematical problem of exploiting a relative dissimilarity representation of signals in a visual informatics mapping model, driven by real-world sonar systems. A realistic noise model is explored and incorporated into non-linear and topographic visualisation algorithms building on the approach of [9]. Concepts are illustrated using a real world dataset of 32 hydrophones monitoring a shallow-water environment in which targets are present and dynamic.

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M3 - Conference publication

AN - SCOPUS:84936803301

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BT - 2014 Sensor Signal Processing for Defence (SSPD)

PB - IEEE

CY - Piscataway, NJ (US)

T2 - 4th conference of the Sensor Signal Processing for Defence

Y2 - 8 September 2014 through 9 September 2014

ER -

Topographic visual analytics of multibeam dynamic SONAR data

Abstract

Conference

Bibliographical note

UN SDGs

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