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Expectation maximization-based passive localization relying on asynchronous receivers:: Centralized versus distributed implementations

Expectation maximization-based passive localization relying on asynchronous receivers:: Centralized versus distributed implementations
Expectation maximization-based passive localization relying on asynchronous receivers:: Centralized versus distributed implementations
This paper considers a passive localization scenario relying on a single transmitter, several receivers and multiple moving targets to be located. The so-called “passive” targets equipped with RFID reflectors are capable of reflecting the signals from the transmitter to the receivers. Existing approaches
assume that the transmitter and receivers are synchronous or quasi-synchronous, which is not always realistic in practical scenarios. Hence, an asynchronous wireless network is considered, where different clock offsets are assumed at different receivers. We propose a centralized expectation maximization-based passive localization method for asynchronous receivers
(EMpLaR) by treating the clock offsets as hidden variables. Thereby, the proposed algorithm makes use of Taylor expansions to arrive at a closed-form maximization. Furthermore, to improve the robustness to link failures and to reduce the energy consumption, we propose a distributed localization approach
based on average consensus formulation to locate the target at each receiver. By applying a quadratic polynomial approximation of the function on which consensus has to be reached, both the computational complexity and the communications overhead are significantly reduced. The Cram ́ r-Rao bound of the target location is derived as a benchmark of our proposed algorithms. Our simulation results show that the proposed centralized and distributed EMpLaR algorithms match the Cram ́ r-Rao bound and significantly improve the localization performance compared to the conventional methods.
0090-6778
Yuan, Weijie
f1d6dc8e-6e97-4c5b-bfc7-78f48efb93b7
Wu, Nan
f26dc0e1-7da9-4c52-a5a8-d6387a8853f2
Etzlinger, Bernhard
0d848d44-1685-480a-8974-e28fe609f206
Li, Yonghui
3065a1c4-56db-4883-89c2-37b72b48f678
Yan, Chaoxing
c7bc0d86-7445-4705-a830-2041c52d9b79
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
Yuan, Weijie
f1d6dc8e-6e97-4c5b-bfc7-78f48efb93b7
Wu, Nan
f26dc0e1-7da9-4c52-a5a8-d6387a8853f2
Etzlinger, Bernhard
0d848d44-1685-480a-8974-e28fe609f206
Li, Yonghui
3065a1c4-56db-4883-89c2-37b72b48f678
Yan, Chaoxing
c7bc0d86-7445-4705-a830-2041c52d9b79
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1

Yuan, Weijie, Wu, Nan, Etzlinger, Bernhard, Li, Yonghui, Yan, Chaoxing and Hanzo, Lajos (2018) Expectation maximization-based passive localization relying on asynchronous receivers:: Centralized versus distributed implementations. IEEE Transactions on Communications.

Record type: Article

Abstract

This paper considers a passive localization scenario relying on a single transmitter, several receivers and multiple moving targets to be located. The so-called “passive” targets equipped with RFID reflectors are capable of reflecting the signals from the transmitter to the receivers. Existing approaches
assume that the transmitter and receivers are synchronous or quasi-synchronous, which is not always realistic in practical scenarios. Hence, an asynchronous wireless network is considered, where different clock offsets are assumed at different receivers. We propose a centralized expectation maximization-based passive localization method for asynchronous receivers
(EMpLaR) by treating the clock offsets as hidden variables. Thereby, the proposed algorithm makes use of Taylor expansions to arrive at a closed-form maximization. Furthermore, to improve the robustness to link failures and to reduce the energy consumption, we propose a distributed localization approach
based on average consensus formulation to locate the target at each receiver. By applying a quadratic polynomial approximation of the function on which consensus has to be reached, both the computational complexity and the communications overhead are significantly reduced. The Cram ́ r-Rao bound of the target location is derived as a benchmark of our proposed algorithms. Our simulation results show that the proposed centralized and distributed EMpLaR algorithms match the Cram ́ r-Rao bound and significantly improve the localization performance compared to the conventional methods.

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Accepted/In Press date: 14 August 2018
e-pub ahead of print date: 21 August 2018

Identifiers

Local EPrints ID: 423235
URI: http://eprints.soton.ac.uk/id/eprint/423235
ISSN: 0090-6778
PURE UUID: c42ec3c7-4e34-4299-b24a-02b15d904f81
ORCID for Lajos Hanzo: ORCID iD orcid.org/0000-0002-2636-5214

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Date deposited: 19 Sep 2018 16:30
Last modified: 23 Jul 2022 01:33

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Contributors

Author: Weijie Yuan
Author: Nan Wu
Author: Bernhard Etzlinger
Author: Yonghui Li
Author: Chaoxing Yan
Author: Lajos Hanzo ORCID iD

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