Standard

Multi-Sensor Task Assignment Using Linear Matrix Inequalities in the Multiple Target Tracking Problem. / Erofeeva, Victoria; Granichin, Oleg; Granichina, Olga.

In: IFAC-PapersOnLine, Vol. 51, No. 15, 2018, p. 880-885.

Research output: Contribution to journal › Article › peer-review

Harvard

Erofeeva, V, Granichin, O & Granichina, O 2018, 'Multi-Sensor Task Assignment Using Linear Matrix Inequalities in the Multiple Target Tracking Problem', IFAC-PapersOnLine, vol. 51, no. 15, pp. 880-885. https://doi.org/10.1016/j.ifacol.2018.09.110

APA

Erofeeva, V., Granichin, O., & Granichina, O. (2018). Multi-Sensor Task Assignment Using Linear Matrix Inequalities in the Multiple Target Tracking Problem. IFAC-PapersOnLine, 51(15), 880-885. https://doi.org/10.1016/j.ifacol.2018.09.110

Vancouver

Erofeeva V, Granichin O, Granichina O. Multi-Sensor Task Assignment Using Linear Matrix Inequalities in the Multiple Target Tracking Problem. IFAC-PapersOnLine. 2018;51(15):880-885. https://doi.org/10.1016/j.ifacol.2018.09.110

Author

Erofeeva, Victoria ; Granichin, Oleg ; Granichina, Olga. / Multi-Sensor Task Assignment Using Linear Matrix Inequalities in the Multiple Target Tracking Problem. In: IFAC-PapersOnLine. 2018 ; Vol. 51, No. 15. pp. 880-885.

BibTeX

@article{dbb34d06827f405baa99d3c5a2157671,
title = "Multi-Sensor Task Assignment Using Linear Matrix Inequalities in the Multiple Target Tracking Problem",
abstract = "Due to significant 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 propose a task assignment algorithm based on linear matrix inequalities (LMI) to reduce the computational complexity and communication load. Simulation results and a comparison with the Kalman filtering strategy confirm the suitability of the approach. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.",
keywords = "sensor network, multiple target tracking, linear matrix inequalities, ellipsoidal approximation, task assignments, WIRELESS SENSOR NETWORKS, ALLOCATION, SELECTION, OPTIMIZATION, SYSTEMS",
author = "Victoria Erofeeva and Oleg Granichin and Olga Granichina",
year = "2018",
doi = "10.1016/j.ifacol.2018.09.110",
language = "Английский",
volume = "51",
pages = "880--885",
journal = "IFAC-PapersOnLine",
issn = "2405-8971",
publisher = "Elsevier",
number = "15",
note = "null ; Conference date: 09-07-2018 Through 11-07-2018",

}

RIS

TY - JOUR

T1 - Multi-Sensor Task Assignment Using Linear Matrix Inequalities in the Multiple Target Tracking Problem

AU - Erofeeva, Victoria

AU - Granichin, Oleg

AU - Granichina, Olga

PY - 2018

Y1 - 2018

N2 - Due to significant 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 propose a task assignment algorithm based on linear matrix inequalities (LMI) to reduce the computational complexity and communication load. Simulation results and a comparison with the Kalman filtering strategy confirm the suitability of the approach. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

AB - Due to significant 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 propose a task assignment algorithm based on linear matrix inequalities (LMI) to reduce the computational complexity and communication load. Simulation results and a comparison with the Kalman filtering strategy confirm the suitability of the approach. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

KW - sensor network

KW - multiple target tracking

KW - linear matrix inequalities

KW - ellipsoidal approximation

KW - task assignments

KW - WIRELESS SENSOR NETWORKS

KW - ALLOCATION

KW - SELECTION

KW - OPTIMIZATION

KW - SYSTEMS

UR - http://www.scopus.com/inward/record.url?scp=85054345255&partnerID=8YFLogxK

UR - http://www.mendeley.com/research/multisensor-task-assignment-using-linear-matrix-inequalities-multiple-target-tracking-problem

U2 - 10.1016/j.ifacol.2018.09.110

DO - 10.1016/j.ifacol.2018.09.110

M3 - статья

AN - SCOPUS:85054345255

VL - 51

SP - 880

EP - 885

JO - IFAC-PapersOnLine

JF - IFAC-PapersOnLine

SN - 2405-8971

IS - 15

Y2 - 9 July 2018 through 11 July 2018

ER -

ID: 35181335