Adaptation of acoustic sensor orientation based on sensor characteristics for improving tracking performance

Jinseok Lee; Sangjin Hong; Junghun Ryu; We Duke Cho

doi:10.1109/MLSP.2008.4685513

Adaptation of acoustic sensor orientation based on sensor characteristics for improving tracking performance

Jinseok Lee
, Sangjin Hong
, Junghun Ryu
, We Duke Cho

Electrical Engineering

Stony Brook University
Ajou University

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

Abstract

This paper addresses the adaptation method of acoustic sensor orientation for improving tracking performance. The orientation adaptation is based on an empirical reception characteristics of the sensor. The study assumes that an object is transmitting Gaussian noise-corrupted signals. In a 3-D space, the observed measurements by the sensor are projected to each of 2-D plane, and the projected measurement variance is significantly reduced by changing the sensor orientation. This paper demonstrates the derivation of the projected measurement variances, and compares to the original measurement variances. The performance of the proposed method is evaluated with Sequential Monte Carlo (SMC) techniques.

Original language	English
Title of host publication	Proceedings of the 2008 IEEE Workshop on Machine Learning for Signal Processing, MLSP 2008
Pages	398-403
Number of pages	6
DOIs	https://doi.org/10.1109/MLSP.2008.4685513
State	Published - 2008
Event	2008 IEEE Workshop on Machine Learning for Signal Processing, MLSP 2008 - Cancun, Mexico Duration: Oct 16 2008 → Oct 19 2008

Publication series

Name	Proceedings of the 2008 IEEE Workshop on Machine Learning for Signal Processing, MLSP 2008

Conference

Conference	2008 IEEE Workshop on Machine Learning for Signal Processing, MLSP 2008
Country/Territory	Mexico
City	Cancun
Period	10/16/08 → 10/19/08

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10.1109/MLSP.2008.4685513

Cite this

Lee, J., Hong, S., Ryu, J., & Cho, W. D. (2008). Adaptation of acoustic sensor orientation based on sensor characteristics for improving tracking performance. In Proceedings of the 2008 IEEE Workshop on Machine Learning for Signal Processing, MLSP 2008 (pp. 398-403). Article 4685513 (Proceedings of the 2008 IEEE Workshop on Machine Learning for Signal Processing, MLSP 2008). https://doi.org/10.1109/MLSP.2008.4685513

@inproceedings{1da6ca47bd5041b48072f1794445925e,

title = "Adaptation of acoustic sensor orientation based on sensor characteristics for improving tracking performance",

abstract = "This paper addresses the adaptation method of acoustic sensor orientation for improving tracking performance. The orientation adaptation is based on an empirical reception characteristics of the sensor. The study assumes that an object is transmitting Gaussian noise-corrupted signals. In a 3-D space, the observed measurements by the sensor are projected to each of 2-D plane, and the projected measurement variance is significantly reduced by changing the sensor orientation. This paper demonstrates the derivation of the projected measurement variances, and compares to the original measurement variances. The performance of the proposed method is evaluated with Sequential Monte Carlo (SMC) techniques.",

author = "Jinseok Lee and Sangjin Hong and Junghun Ryu and Cho, \{We Duke\}",

year = "2008",

doi = "10.1109/MLSP.2008.4685513",

language = "English",

isbn = "9781424423767",

series = "Proceedings of the 2008 IEEE Workshop on Machine Learning for Signal Processing, MLSP 2008",

pages = "398--403",

booktitle = "Proceedings of the 2008 IEEE Workshop on Machine Learning for Signal Processing, MLSP 2008",

note = "2008 IEEE Workshop on Machine Learning for Signal Processing, MLSP 2008 ; Conference date: 16-10-2008 Through 19-10-2008",

}

Lee, J, Hong, S, Ryu, J & Cho, WD 2008, Adaptation of acoustic sensor orientation based on sensor characteristics for improving tracking performance. in Proceedings of the 2008 IEEE Workshop on Machine Learning for Signal Processing, MLSP 2008., 4685513, Proceedings of the 2008 IEEE Workshop on Machine Learning for Signal Processing, MLSP 2008, pp. 398-403, 2008 IEEE Workshop on Machine Learning for Signal Processing, MLSP 2008, Cancun, Mexico, 10/16/08. https://doi.org/10.1109/MLSP.2008.4685513

Adaptation of acoustic sensor orientation based on sensor characteristics for improving tracking performance. / Lee, Jinseok; Hong, Sangjin; Ryu, Junghun et al.
Proceedings of the 2008 IEEE Workshop on Machine Learning for Signal Processing, MLSP 2008. 2008. p. 398-403 4685513 (Proceedings of the 2008 IEEE Workshop on Machine Learning for Signal Processing, MLSP 2008).

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

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AU - Hong, Sangjin

AU - Ryu, Junghun

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N2 - This paper addresses the adaptation method of acoustic sensor orientation for improving tracking performance. The orientation adaptation is based on an empirical reception characteristics of the sensor. The study assumes that an object is transmitting Gaussian noise-corrupted signals. In a 3-D space, the observed measurements by the sensor are projected to each of 2-D plane, and the projected measurement variance is significantly reduced by changing the sensor orientation. This paper demonstrates the derivation of the projected measurement variances, and compares to the original measurement variances. The performance of the proposed method is evaluated with Sequential Monte Carlo (SMC) techniques.

AB - This paper addresses the adaptation method of acoustic sensor orientation for improving tracking performance. The orientation adaptation is based on an empirical reception characteristics of the sensor. The study assumes that an object is transmitting Gaussian noise-corrupted signals. In a 3-D space, the observed measurements by the sensor are projected to each of 2-D plane, and the projected measurement variance is significantly reduced by changing the sensor orientation. This paper demonstrates the derivation of the projected measurement variances, and compares to the original measurement variances. The performance of the proposed method is evaluated with Sequential Monte Carlo (SMC) techniques.

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DO - 10.1109/MLSP.2008.4685513

M3 - Conference contribution

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T3 - Proceedings of the 2008 IEEE Workshop on Machine Learning for Signal Processing, MLSP 2008

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EP - 403

BT - Proceedings of the 2008 IEEE Workshop on Machine Learning for Signal Processing, MLSP 2008

T2 - 2008 IEEE Workshop on Machine Learning for Signal Processing, MLSP 2008

Y2 - 16 October 2008 through 19 October 2008

ER -

Lee J, Hong S, Ryu J, Cho WD. Adaptation of acoustic sensor orientation based on sensor characteristics for improving tracking performance. In Proceedings of the 2008 IEEE Workshop on Machine Learning for Signal Processing, MLSP 2008. 2008. p. 398-403. 4685513. (Proceedings of the 2008 IEEE Workshop on Machine Learning for Signal Processing, MLSP 2008). doi: 10.1109/MLSP.2008.4685513

Adaptation of acoustic sensor orientation based on sensor characteristics for improving tracking performance

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