### Abstract

Acoustic source localization is one of the interesting applications of sensor networks. Localization algorithms that use acoustic signal energy measurements at individual sensor nodes are proposed. The maximum likelihood (ML) algorithm is known as an algorithm for source localization. The ML algorithm has high accuracy to estimate source location, however the calculation amount of the ML algorithm is large. The expectation-maximization (EM) algorithm is proposed to realize the ML algorithm with less amount of calculation. An EM algorithm processed at a center, that is, the centralized EM algorithm is proposed in which each sensor node sends observed information to the center. The total cost of the centralized data processing is expensive, because the communication cost is large when the transmission distance from each sensor node to the center is long. On the other hand, the distributed data processing can reduce the transmission cost and thus the total cost, because data is processed in each sensor node and thus the amount of communication can be reduced. In this paper, we propose a distributed EM algorithm for acoustic source localization that is applicable to a source with unknown signal energy. We show that the proposed algorithm has high accuracy and reduces the communication cost.

Original language | English |
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Title of host publication | IEEE Vehicular Technology Conference |

Pages | 2494-2498 |

Number of pages | 5 |

DOIs | |

Publication status | Published - 2006 |

Event | 2006 IEEE 64th Vehicular Technology Conference, VTC-2006 Fall - Montreal, QC, Canada Duration: 2006 Sep 25 → 2006 Sep 28 |

### Other

Other | 2006 IEEE 64th Vehicular Technology Conference, VTC-2006 Fall |
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Country | Canada |

City | Montreal, QC |

Period | 06/9/25 → 06/9/28 |

### Fingerprint

### ASJC Scopus subject areas

- Electrical and Electronic Engineering

### Cite this

*IEEE Vehicular Technology Conference*(pp. 2494-2498). [4109778] https://doi.org/10.1109/VTCF.2006.513

**Distributed em algorithms for acoustic source localization in sensor networks.** / Kitakoga, Noriaki; Ohtsuki, Tomoaki.

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

*IEEE Vehicular Technology Conference.*, 4109778, pp. 2494-2498, 2006 IEEE 64th Vehicular Technology Conference, VTC-2006 Fall, Montreal, QC, Canada, 06/9/25. https://doi.org/10.1109/VTCF.2006.513

}

TY - GEN

T1 - Distributed em algorithms for acoustic source localization in sensor networks

AU - Kitakoga, Noriaki

AU - Ohtsuki, Tomoaki

PY - 2006

Y1 - 2006

N2 - Acoustic source localization is one of the interesting applications of sensor networks. Localization algorithms that use acoustic signal energy measurements at individual sensor nodes are proposed. The maximum likelihood (ML) algorithm is known as an algorithm for source localization. The ML algorithm has high accuracy to estimate source location, however the calculation amount of the ML algorithm is large. The expectation-maximization (EM) algorithm is proposed to realize the ML algorithm with less amount of calculation. An EM algorithm processed at a center, that is, the centralized EM algorithm is proposed in which each sensor node sends observed information to the center. The total cost of the centralized data processing is expensive, because the communication cost is large when the transmission distance from each sensor node to the center is long. On the other hand, the distributed data processing can reduce the transmission cost and thus the total cost, because data is processed in each sensor node and thus the amount of communication can be reduced. In this paper, we propose a distributed EM algorithm for acoustic source localization that is applicable to a source with unknown signal energy. We show that the proposed algorithm has high accuracy and reduces the communication cost.

AB - Acoustic source localization is one of the interesting applications of sensor networks. Localization algorithms that use acoustic signal energy measurements at individual sensor nodes are proposed. The maximum likelihood (ML) algorithm is known as an algorithm for source localization. The ML algorithm has high accuracy to estimate source location, however the calculation amount of the ML algorithm is large. The expectation-maximization (EM) algorithm is proposed to realize the ML algorithm with less amount of calculation. An EM algorithm processed at a center, that is, the centralized EM algorithm is proposed in which each sensor node sends observed information to the center. The total cost of the centralized data processing is expensive, because the communication cost is large when the transmission distance from each sensor node to the center is long. On the other hand, the distributed data processing can reduce the transmission cost and thus the total cost, because data is processed in each sensor node and thus the amount of communication can be reduced. In this paper, we propose a distributed EM algorithm for acoustic source localization that is applicable to a source with unknown signal energy. We show that the proposed algorithm has high accuracy and reduces the communication cost.

UR - http://www.scopus.com/inward/record.url?scp=34548849460&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=34548849460&partnerID=8YFLogxK

U2 - 10.1109/VTCF.2006.513

DO - 10.1109/VTCF.2006.513

M3 - Conference contribution

AN - SCOPUS:34548849460

SN - 1424400635

SN - 9781424400638

SP - 2494

EP - 2498

BT - IEEE Vehicular Technology Conference

ER -