Opportunistic doppler-only indoor localization via passive radar

Wenda Li; Bo Tan; Robert Piechocki

doi:10.1109/dasc/picom/datacom/cyberscitec.2018.00093

Opportunistic doppler-only indoor localization via passive radar

Wenda Li
, Bo Tan
, Robert Piechocki

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

4 Citations (Scopus)

Abstract

Indoor localization is a vital ingredient for many e-Healthcare and Ambient Assisted Living (AAL) applications. However, accurate, low power and user acceptable solutions remain elusive. In this paper, we present a novel opportunistic system which estimates the localization information based only on the Doppler information from the user. The Doppler information is collected using the passive radar technique that deploys the RF energy transfer signal which originally intended only to deliver energy to home IoT devices. A low complexity Extended Kalman Filter (EKF) is also proposed to predict and track the user's location. A real-time system has been built based on the software defined radio (SDR) platform to verify the proposed methodology. Experimental results indicate that the proposed concepts can be used for indoor localization with a high degree of accuracy.

Original language	English
Title of host publication	Proceedings of IEEE 16th International Conference on Dependable, Autonomic and Secure Computing
Publisher	IEEE
Pages	467-473
Number of pages	7
ISBN (Print)	9781538675182
DOIs	https://doi.org/10.1109/dasc/picom/datacom/cyberscitec.2018.00093
Publication status	Published - Aug 2018
Event	IEEE 16th International Conference on Dependable, Autonomic and Secure Computing - Athens, Greece Duration: 12 Aug 2018 → 15 Aug 2018

Conference

Conference	IEEE 16th International Conference on Dependable, Autonomic and Secure Computing
Abbreviated title	DASC-PICom-DataCom-CyberSciTec 2018
Country/Territory	Greece
City	Athens
Period	12/08/18 → 15/08/18

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10.1109/dasc/picom/datacom/cyberscitec.2018.00093

Cite this

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title = "Opportunistic doppler-only indoor localization via passive radar",

abstract = "Indoor localization is a vital ingredient for many e-Healthcare and Ambient Assisted Living (AAL) applications. However, accurate, low power and user acceptable solutions remain elusive. In this paper, we present a novel opportunistic system which estimates the localization information based only on the Doppler information from the user. The Doppler information is collected using the passive radar technique that deploys the RF energy transfer signal which originally intended only to deliver energy to home IoT devices. A low complexity Extended Kalman Filter (EKF) is also proposed to predict and track the user's location. A real-time system has been built based on the software defined radio (SDR) platform to verify the proposed methodology. Experimental results indicate that the proposed concepts can be used for indoor localization with a high degree of accuracy.",

author = "Wenda Li and Bo Tan and Robert Piechocki",

year = "2018",

month = aug,

doi = "10.1109/dasc/picom/datacom/cyberscitec.2018.00093",

language = "English",

isbn = "9781538675182",

pages = "467--473",

booktitle = "Proceedings of IEEE 16th International Conference on Dependable, Autonomic and Secure Computing",

publisher = "IEEE",

note = "IEEE 16th International Conference on Dependable, Autonomic and Secure Computing, DASC-PICom-DataCom-CyberSciTec 2018 ; Conference date: 12-08-2018 Through 15-08-2018",

}

Li, W, Tan, B & Piechocki, R 2018, Opportunistic doppler-only indoor localization via passive radar. in Proceedings of IEEE 16th International Conference on Dependable, Autonomic and Secure Computing., 8511936, IEEE, pp. 467-473, IEEE 16th International Conference on Dependable, Autonomic and Secure Computing, Athens, Greece, 12/08/18. https://doi.org/10.1109/dasc/picom/datacom/cyberscitec.2018.00093

TY - GEN

T1 - Opportunistic doppler-only indoor localization via passive radar

AU - Li, Wenda

AU - Tan, Bo

AU - Piechocki, Robert

PY - 2018/8

Y1 - 2018/8

N2 - Indoor localization is a vital ingredient for many e-Healthcare and Ambient Assisted Living (AAL) applications. However, accurate, low power and user acceptable solutions remain elusive. In this paper, we present a novel opportunistic system which estimates the localization information based only on the Doppler information from the user. The Doppler information is collected using the passive radar technique that deploys the RF energy transfer signal which originally intended only to deliver energy to home IoT devices. A low complexity Extended Kalman Filter (EKF) is also proposed to predict and track the user's location. A real-time system has been built based on the software defined radio (SDR) platform to verify the proposed methodology. Experimental results indicate that the proposed concepts can be used for indoor localization with a high degree of accuracy.

AB - Indoor localization is a vital ingredient for many e-Healthcare and Ambient Assisted Living (AAL) applications. However, accurate, low power and user acceptable solutions remain elusive. In this paper, we present a novel opportunistic system which estimates the localization information based only on the Doppler information from the user. The Doppler information is collected using the passive radar technique that deploys the RF energy transfer signal which originally intended only to deliver energy to home IoT devices. A low complexity Extended Kalman Filter (EKF) is also proposed to predict and track the user's location. A real-time system has been built based on the software defined radio (SDR) platform to verify the proposed methodology. Experimental results indicate that the proposed concepts can be used for indoor localization with a high degree of accuracy.

U2 - 10.1109/dasc/picom/datacom/cyberscitec.2018.00093

DO - 10.1109/dasc/picom/datacom/cyberscitec.2018.00093

M3 - Conference contribution

SN - 9781538675182

SP - 467

EP - 473

BT - Proceedings of IEEE 16th International Conference on Dependable, Autonomic and Secure Computing

PB - IEEE

T2 - IEEE 16th International Conference on Dependable, Autonomic and Secure Computing

Y2 - 12 August 2018 through 15 August 2018

ER -

Opportunistic doppler-only indoor localization via passive radar

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