### Abstract

In this paper, we propose a novel myopic sensor scheduling methodology for tracking a target moving through a network of energy-constrained acoustic sensors. Specifically, we address the problem of activating the minimum-energy combination of sensors in a network that maintains a desired squared-error accuracy in the target's position estimate. We first formulate the scheduling problem as a binary (0-1) nonlinear programming (NLP) problem. Using a linearization technique, we then convert the 0-1 NLP problem into a 0-1 mixed integer programming (MIP) problem. We solve the reformulated 0-1 MIP problem using a linear programming relaxation based branch-and-bound technique. We demonstrate through Monte Carlo simulations that our proposed MIP scheduling method is very computational efficient as we can find optimal solutions to scheduling problems involving 50-60 sensors with processing time in the order of seconds.

Original language | English (US) |
---|---|

Title of host publication | 2006 IEEE Sensor Array and Multichannel Signal Processing Workshop Proceedings, SAM 2006 |

Pages | 471-475 |

Number of pages | 5 |

State | Published - 2006 |

Event | 4th IEEE Sensor Array and Multichannel Signal Processing Workshop Proceedings, SAM 2006 - Waltham, MA, United States Duration: Jul 12 2006 → Jul 14 2006 |

### Other

Other | 4th IEEE Sensor Array and Multichannel Signal Processing Workshop Proceedings, SAM 2006 |
---|---|

Country | United States |

City | Waltham, MA |

Period | 7/12/06 → 7/14/06 |

### Fingerprint

### ASJC Scopus subject areas

- Signal Processing
- Control and Systems Engineering
- Electrical and Electronic Engineering

### Cite this

*2006 IEEE Sensor Array and Multichannel Signal Processing Workshop Proceedings, SAM 2006*(pp. 471-475)

**Sensor scheduling using a 0-1 mixed integer programming framework.** / Chhetri, Amit S.; Morrell, Darryl; Papandreou-Suppappola, Antonia.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*2006 IEEE Sensor Array and Multichannel Signal Processing Workshop Proceedings, SAM 2006.*pp. 471-475, 4th IEEE Sensor Array and Multichannel Signal Processing Workshop Proceedings, SAM 2006, Waltham, MA, United States, 7/12/06.

}

TY - GEN

T1 - Sensor scheduling using a 0-1 mixed integer programming framework

AU - Chhetri, Amit S.

AU - Morrell, Darryl

AU - Papandreou-Suppappola, Antonia

PY - 2006

Y1 - 2006

N2 - In this paper, we propose a novel myopic sensor scheduling methodology for tracking a target moving through a network of energy-constrained acoustic sensors. Specifically, we address the problem of activating the minimum-energy combination of sensors in a network that maintains a desired squared-error accuracy in the target's position estimate. We first formulate the scheduling problem as a binary (0-1) nonlinear programming (NLP) problem. Using a linearization technique, we then convert the 0-1 NLP problem into a 0-1 mixed integer programming (MIP) problem. We solve the reformulated 0-1 MIP problem using a linear programming relaxation based branch-and-bound technique. We demonstrate through Monte Carlo simulations that our proposed MIP scheduling method is very computational efficient as we can find optimal solutions to scheduling problems involving 50-60 sensors with processing time in the order of seconds.

AB - In this paper, we propose a novel myopic sensor scheduling methodology for tracking a target moving through a network of energy-constrained acoustic sensors. Specifically, we address the problem of activating the minimum-energy combination of sensors in a network that maintains a desired squared-error accuracy in the target's position estimate. We first formulate the scheduling problem as a binary (0-1) nonlinear programming (NLP) problem. Using a linearization technique, we then convert the 0-1 NLP problem into a 0-1 mixed integer programming (MIP) problem. We solve the reformulated 0-1 MIP problem using a linear programming relaxation based branch-and-bound technique. We demonstrate through Monte Carlo simulations that our proposed MIP scheduling method is very computational efficient as we can find optimal solutions to scheduling problems involving 50-60 sensors with processing time in the order of seconds.

UR - http://www.scopus.com/inward/record.url?scp=34250615438&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=34250615438&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:34250615438

SN - 1424403081

SN - 9781424403080

SP - 471

EP - 475

BT - 2006 IEEE Sensor Array and Multichannel Signal Processing Workshop Proceedings, SAM 2006

ER -