2 Citations (Scopus)

Abstract

Directional sensors are gaining importance due to applications, including surveillance, detection, and tracking. Such sensors have a limited field of view and a discrete set of directions they can be pointed to. The directional sensor control problem (DSCP) consists in assigning a direction of view to each sensor. The location of the targets is known with uncertainty given by a joint a priori Gaussian distribution, while the sensor locations are known exactly. In this paper, we study the exact and heuristic approaches for the DSCP with the goal of maximizing information gain on the location of a given set of immobile target objects. In particular, we propose an exact mixed integer convex programming (MICP) formulation to be solved by a black-box MICP solver and several metaheuristic approaches based on local search. A computational evaluation shows the very good performance of both methods.

Original languageEnglish (US)
Article number7174980
Pages (from-to)6633-6639
Number of pages7
JournalIEEE Sensors Journal
Volume15
Issue number11
DOIs
StatePublished - Nov 1 2015

Fingerprint

sensors
Sensors
Convex optimization
programming
integers
Gaussian distribution
surveillance
normal density functions
field of view
boxes
formulations
evaluation

Keywords

  • Benders decomposition
  • directional sensors
  • metaheuristics
  • Mixed integer convex programming

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Instrumentation

Cite this

Exact and heuristic approaches for directional sensor control. / Mittelmann, Hans; Salvagnin, Domenico.

In: IEEE Sensors Journal, Vol. 15, No. 11, 7174980, 01.11.2015, p. 6633-6639.

Research output: Contribution to journalArticle

Mittelmann, Hans ; Salvagnin, Domenico. / Exact and heuristic approaches for directional sensor control. In: IEEE Sensors Journal. 2015 ; Vol. 15, No. 11. pp. 6633-6639.
@article{9b5a0e11cf484e2faaf5941eaa1f4258,
title = "Exact and heuristic approaches for directional sensor control",
abstract = "Directional sensors are gaining importance due to applications, including surveillance, detection, and tracking. Such sensors have a limited field of view and a discrete set of directions they can be pointed to. The directional sensor control problem (DSCP) consists in assigning a direction of view to each sensor. The location of the targets is known with uncertainty given by a joint a priori Gaussian distribution, while the sensor locations are known exactly. In this paper, we study the exact and heuristic approaches for the DSCP with the goal of maximizing information gain on the location of a given set of immobile target objects. In particular, we propose an exact mixed integer convex programming (MICP) formulation to be solved by a black-box MICP solver and several metaheuristic approaches based on local search. A computational evaluation shows the very good performance of both methods.",
keywords = "Benders decomposition, directional sensors, metaheuristics, Mixed integer convex programming",
author = "Hans Mittelmann and Domenico Salvagnin",
year = "2015",
month = "11",
day = "1",
doi = "10.1109/JSEN.2015.2464155",
language = "English (US)",
volume = "15",
pages = "6633--6639",
journal = "IEEE Sensors Journal",
issn = "1530-437X",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "11",

}

TY - JOUR

T1 - Exact and heuristic approaches for directional sensor control

AU - Mittelmann, Hans

AU - Salvagnin, Domenico

PY - 2015/11/1

Y1 - 2015/11/1

N2 - Directional sensors are gaining importance due to applications, including surveillance, detection, and tracking. Such sensors have a limited field of view and a discrete set of directions they can be pointed to. The directional sensor control problem (DSCP) consists in assigning a direction of view to each sensor. The location of the targets is known with uncertainty given by a joint a priori Gaussian distribution, while the sensor locations are known exactly. In this paper, we study the exact and heuristic approaches for the DSCP with the goal of maximizing information gain on the location of a given set of immobile target objects. In particular, we propose an exact mixed integer convex programming (MICP) formulation to be solved by a black-box MICP solver and several metaheuristic approaches based on local search. A computational evaluation shows the very good performance of both methods.

AB - Directional sensors are gaining importance due to applications, including surveillance, detection, and tracking. Such sensors have a limited field of view and a discrete set of directions they can be pointed to. The directional sensor control problem (DSCP) consists in assigning a direction of view to each sensor. The location of the targets is known with uncertainty given by a joint a priori Gaussian distribution, while the sensor locations are known exactly. In this paper, we study the exact and heuristic approaches for the DSCP with the goal of maximizing information gain on the location of a given set of immobile target objects. In particular, we propose an exact mixed integer convex programming (MICP) formulation to be solved by a black-box MICP solver and several metaheuristic approaches based on local search. A computational evaluation shows the very good performance of both methods.

KW - Benders decomposition

KW - directional sensors

KW - metaheuristics

KW - Mixed integer convex programming

UR - http://www.scopus.com/inward/record.url?scp=84961117096&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84961117096&partnerID=8YFLogxK

U2 - 10.1109/JSEN.2015.2464155

DO - 10.1109/JSEN.2015.2464155

M3 - Article

AN - SCOPUS:84961117096

VL - 15

SP - 6633

EP - 6639

JO - IEEE Sensors Journal

JF - IEEE Sensors Journal

SN - 1530-437X

IS - 11

M1 - 7174980

ER -