Noise reduction for variance-based radio tomographic localization

Yang Zhao; Neal Patwari

doi:10.1109/SAHCN.2011.5984889

Noise reduction for variance-based radio tomographic localization

Yang Zhao^*
, Neal Patwari

^*Corresponding author for this work

University of Utah

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

Abstract

We propose to demonstrate a new radio tomographic localization algorithm - subspace variance-based radio tomography (SubVRT), which is more robust to RSS variations caused by objects that are intrinsic parts of the environment. We first introduce the subspace decomposition method, then we derive the formulations of SubVRT, and finally we describe the demonstration setup, requirements and procedures.

Original language	English
Title of host publication	2011 8th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks, SECON 2011
Pages	155-157
Number of pages	3
DOIs	https://doi.org/10.1109/SAHCN.2011.5984889
State	Published - 2011
Externally published	Yes
Event	2011 8th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks, SECON 2011 - Salt Lake City, UT, United States Duration: 27 Jun 2011 → 30 Jun 2011

Publication series

Name	2011 8th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks, SECON 2011

Conference

Conference	2011 8th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks, SECON 2011
Country/Territory	United States
City	Salt Lake City, UT
Period	27/06/11 → 30/06/11

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10.1109/SAHCN.2011.5984889

Cite this

Zhao, Y., & Patwari, N. (2011). Noise reduction for variance-based radio tomographic localization. In 2011 8th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks, SECON 2011 (pp. 155-157). Article 5984889 (2011 8th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks, SECON 2011). https://doi.org/10.1109/SAHCN.2011.5984889

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title = "Noise reduction for variance-based radio tomographic localization",

abstract = "We propose to demonstrate a new radio tomographic localization algorithm - subspace variance-based radio tomography (SubVRT), which is more robust to RSS variations caused by objects that are intrinsic parts of the environment. We first introduce the subspace decomposition method, then we derive the formulations of SubVRT, and finally we describe the demonstration setup, requirements and procedures.",

author = "Yang Zhao and Neal Patwari",

year = "2011",

doi = "10.1109/SAHCN.2011.5984889",

language = "英语",

isbn = "9781457700934",

series = "2011 8th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks, SECON 2011",

pages = "155--157",

booktitle = "2011 8th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks, SECON 2011",

note = "2011 8th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks, SECON 2011 ; Conference date: 27-06-2011 Through 30-06-2011",

}

Zhao, Y & Patwari, N 2011, Noise reduction for variance-based radio tomographic localization. in 2011 8th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks, SECON 2011., 5984889, 2011 8th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks, SECON 2011, pp. 155-157, 2011 8th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks, SECON 2011, Salt Lake City, UT, United States, 27/06/11. https://doi.org/10.1109/SAHCN.2011.5984889

Noise reduction for variance-based radio tomographic localization. / Zhao, Yang; Patwari, Neal.
2011 8th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks, SECON 2011. 2011. p. 155-157 5984889 (2011 8th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks, SECON 2011).

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

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AU - Patwari, Neal

PY - 2011

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N2 - We propose to demonstrate a new radio tomographic localization algorithm - subspace variance-based radio tomography (SubVRT), which is more robust to RSS variations caused by objects that are intrinsic parts of the environment. We first introduce the subspace decomposition method, then we derive the formulations of SubVRT, and finally we describe the demonstration setup, requirements and procedures.

AB - We propose to demonstrate a new radio tomographic localization algorithm - subspace variance-based radio tomography (SubVRT), which is more robust to RSS variations caused by objects that are intrinsic parts of the environment. We first introduce the subspace decomposition method, then we derive the formulations of SubVRT, and finally we describe the demonstration setup, requirements and procedures.

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DO - 10.1109/SAHCN.2011.5984889

M3 - 会议稿件

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BT - 2011 8th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks, SECON 2011

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Y2 - 27 June 2011 through 30 June 2011

ER -

Zhao Y, Patwari N. Noise reduction for variance-based radio tomographic localization. In 2011 8th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks, SECON 2011. 2011. p. 155-157. 5984889. (2011 8th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks, SECON 2011). doi: 10.1109/SAHCN.2011.5984889

Noise reduction for variance-based radio tomographic localization

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