Source localization via randomly distributed sensors

Itsik Bergel; Yair Noam

doi:10.1109/SPAWC.2016.7536794

Source localization via randomly distributed sensors

Itsik Bergel, Yair Noam

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

3 Scopus citations

Abstract

We present novel lower bounds on the mean-square source-localization error via a network where the sensors are deployed randomly (e.g., scattered from the air). The sensor locations are modeled as a homogenous Poisson point process. We present CRB-type bounds on the expectation of the localization square error, which is not a function of a particular sensor configuration, but rather of the sensor statistics. Thus, it can be evaluated prior to the sensor deployment and provide insights into design issues such as the necessary sensor density. The derived bounds are simple for evaluation, while providing a good prediction of the actual network performance.

Original language	English
Title of host publication	SPAWC 2016 - 17th IEEE International Workshop on Signal Processing Advances in Wireless Communications
Publisher	Institute of Electrical and Electronics Engineers
ISBN (Electronic)	9781509017492
DOIs	https://doi.org/10.1109/SPAWC.2016.7536794
State	Published - 9 Aug 2016
Externally published	Yes
Event	17th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2016 - Edinburgh, United Kingdom Duration: 3 Jul 2016 → 6 Jul 2016

Publication series

Name	IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC
Volume	2016-August

Conference

Conference	17th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2016
Country/Territory	United Kingdom
City	Edinburgh
Period	3/07/16 → 6/07/16

ASJC Scopus subject areas

Electrical and Electronic Engineering
Computer Science Applications
Information Systems

Access to Document

10.1109/SPAWC.2016.7536794

Cite this

Bergel, I., & Noam, Y. (2016). Source localization via randomly distributed sensors. In SPAWC 2016 - 17th IEEE International Workshop on Signal Processing Advances in Wireless Communications Article 7536794 (IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC; Vol. 2016-August). Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/SPAWC.2016.7536794

@inproceedings{91659326b2d940438ddc72fe64d66ca8,

title = "Source localization via randomly distributed sensors",

abstract = "We present novel lower bounds on the mean-square source-localization error via a network where the sensors are deployed randomly (e.g., scattered from the air). The sensor locations are modeled as a homogenous Poisson point process. We present CRB-type bounds on the expectation of the localization square error, which is not a function of a particular sensor configuration, but rather of the sensor statistics. Thus, it can be evaluated prior to the sensor deployment and provide insights into design issues such as the necessary sensor density. The derived bounds are simple for evaluation, while providing a good prediction of the actual network performance.",

author = "Itsik Bergel and Yair Noam",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 17th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2016 ; Conference date: 03-07-2016 Through 06-07-2016",

year = "2016",

month = aug,

day = "9",

doi = "10.1109/SPAWC.2016.7536794",

language = "English",

series = "IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC",

publisher = "Institute of Electrical and Electronics Engineers",

booktitle = "SPAWC 2016 - 17th IEEE International Workshop on Signal Processing Advances in Wireless Communications",

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}

Bergel, I & Noam, Y 2016, Source localization via randomly distributed sensors. in SPAWC 2016 - 17th IEEE International Workshop on Signal Processing Advances in Wireless Communications., 7536794, IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC, vol. 2016-August, Institute of Electrical and Electronics Engineers, 17th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2016, Edinburgh, United Kingdom, 3/07/16. https://doi.org/10.1109/SPAWC.2016.7536794

Source localization via randomly distributed sensors. / Bergel, Itsik; Noam, Yair.
SPAWC 2016 - 17th IEEE International Workshop on Signal Processing Advances in Wireless Communications. Institute of Electrical and Electronics Engineers, 2016. 7536794 (IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC; Vol. 2016-August).

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

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PY - 2016/8/9

Y1 - 2016/8/9

N2 - We present novel lower bounds on the mean-square source-localization error via a network where the sensors are deployed randomly (e.g., scattered from the air). The sensor locations are modeled as a homogenous Poisson point process. We present CRB-type bounds on the expectation of the localization square error, which is not a function of a particular sensor configuration, but rather of the sensor statistics. Thus, it can be evaluated prior to the sensor deployment and provide insights into design issues such as the necessary sensor density. The derived bounds are simple for evaluation, while providing a good prediction of the actual network performance.

AB - We present novel lower bounds on the mean-square source-localization error via a network where the sensors are deployed randomly (e.g., scattered from the air). The sensor locations are modeled as a homogenous Poisson point process. We present CRB-type bounds on the expectation of the localization square error, which is not a function of a particular sensor configuration, but rather of the sensor statistics. Thus, it can be evaluated prior to the sensor deployment and provide insights into design issues such as the necessary sensor density. The derived bounds are simple for evaluation, while providing a good prediction of the actual network performance.

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M3 - Conference contribution

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T3 - IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC

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Y2 - 3 July 2016 through 6 July 2016

ER -

Source localization via randomly distributed sensors

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