Comparison of multi-sensor task assignment inequalities vs. brute force methods: linear matrix

Олег Николаевич Граничин, Виктория Александровна Ерофеева, Анна Васильевна Леонова

Research output

Abstract

Due to signicant advancements in embedded systems, sensor devices, and wireless
communication technology, sensor networks have been attracting widespread attention in areas
such as target tracking, monitoring, and surveillance. Technological advancements made it
possible to deploy a large number of inexpensive but technically advanced sensors to cover wide
areas. However, when a tracking system has to track a large number of targets, the computation
and communication loads arise. In this paper, we compare two task assignment methods that
might be used in the multiple target tracking problem. The rst one is the brute force method
and the second one is based on linear matrix inequalities. We provide performance and load
testing results for these methods.
Original languageEnglish
Pages (from-to)648-653.
Number of pages6
JournalIFAC-PapersOnLine
Publication statusPublished - 19 Oct 2018

Cite this

@article{1a39e1d04cd64a8c888f3182d4a48edc,
title = "Comparison of multi-sensor task assignment inequalities vs. brute force methods: linear matrix",
abstract = "Due to signicant advancements in embedded systems, sensor devices, and wirelesscommunication technology, sensor networks have been attracting widespread attention in areassuch as target tracking, monitoring, and surveillance. Technological advancements made itpossible to deploy a large number of inexpensive but technically advanced sensors to cover wideareas. However, when a tracking system has to track a large number of targets, the computationand communication loads arise. In this paper, we compare two task assignment methods thatmight be used in the multiple target tracking problem. The rst one is the brute force methodand the second one is based on linear matrix inequalities. We provide performance and loadtesting results for these methods.",
keywords = "sensor network, task assignments, multiple target tracking, linear matrix inequalities, ellipsoidal approximation, brute force",
author = "Граничин, {Олег Николаевич} and Ерофеева, {Виктория Александровна} and Леонова, {Анна Васильевна}",
year = "2018",
month = "10",
day = "19",
language = "English",
pages = "648--653.",
journal = "IFAC-PapersOnLine",
issn = "2405-8963",
publisher = "Elsevier",

}

TY - JOUR

T1 - Comparison of multi-sensor task assignment inequalities vs. brute force methods: linear matrix

AU - Граничин, Олег Николаевич

AU - Ерофеева, Виктория Александровна

AU - Леонова, Анна Васильевна

PY - 2018/10/19

Y1 - 2018/10/19

N2 - Due to signicant advancements in embedded systems, sensor devices, and wirelesscommunication technology, sensor networks have been attracting widespread attention in areassuch as target tracking, monitoring, and surveillance. Technological advancements made itpossible to deploy a large number of inexpensive but technically advanced sensors to cover wideareas. However, when a tracking system has to track a large number of targets, the computationand communication loads arise. In this paper, we compare two task assignment methods thatmight be used in the multiple target tracking problem. The rst one is the brute force methodand the second one is based on linear matrix inequalities. We provide performance and loadtesting results for these methods.

AB - Due to signicant advancements in embedded systems, sensor devices, and wirelesscommunication technology, sensor networks have been attracting widespread attention in areassuch as target tracking, monitoring, and surveillance. Technological advancements made itpossible to deploy a large number of inexpensive but technically advanced sensors to cover wideareas. However, when a tracking system has to track a large number of targets, the computationand communication loads arise. In this paper, we compare two task assignment methods thatmight be used in the multiple target tracking problem. The rst one is the brute force methodand the second one is based on linear matrix inequalities. We provide performance and loadtesting results for these methods.

KW - sensor network, task assignments, multiple target tracking, linear matrix inequalities, ellipsoidal approximation, brute force

M3 - Conference article

SP - 648-653.

JO - IFAC-PapersOnLine

JF - IFAC-PapersOnLine

SN - 2405-8963

ER -