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Sensors 2017, 17(11), 2690; https://doi.org/10.3390/s17112690

Target Tracking with Sensor Navigation Using Coupled RSS and AoA Measurements

1
ISR/IST, LARSyS, Universidade de Lisboa, 1049-001 Lisbon, Portugal
2
CICANT-CIC.DIGITAL, Universidade Lusófona de Humanidades e Tecnologias, Campo Grande 376, 1749-024 Lisboa, Portugal
3
CTS/UNINOVA, Campus da FCT/UNL, Monte de Caparica, 2829-516 Caparica, Portugal
4
Instituto de Telecomunicações, Av. Rovisco Pais 1, Torre Norte, piso 10, 1049-001 Lisboa, Portugal
5
Dep.o de Eng.a Electrotécnica, FCT/UNL, 2829-516 Caparica, Portugal
*
Author to whom correspondence should be addressed.
Received: 20 October 2017 / Revised: 10 November 2017 / Accepted: 16 November 2017 / Published: 21 November 2017
(This article belongs to the Section Physical Sensors)
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Abstract

This work addresses the problem of tracking a signal-emitting mobile target in wireless sensor networks (WSNs) with navigated mobile sensors. The sensors are properly equipped to acquire received signal strength (RSS) and angle of arrival (AoA) measurements from the received signal, while the target transmit power is assumed not known. We start by showing how to linearize the highly non-linear measurement model. Then, by employing a Bayesian approach, we combine the linearized observation model with prior knowledge extracted from the state transition model. Based on the maximum a posteriori (MAP) principle and the Kalman filtering (KF) framework, we propose new MAP and KF algorithms, respectively. We also propose a simple and efficient mobile sensor navigation procedure, which allows us to further enhance the estimation accuracy of our algorithms with a reduced number of sensors. Model flaws, which result in imperfect knowledge about the path loss exponent (PLE) and the true mobile sensors’ locations, are taken into consideration. We have carried out an extensive simulation study, and our results confirm the superiority of the proposed algorithms, as well as the effectiveness of the proposed navigation routine. View Full-Text
Keywords: target tracking; sensor navigation; received signal strength (RSS); angle of arrival (AoA); maximum a posteriori (MAP) estimator; Kalman filter (KF) target tracking; sensor navigation; received signal strength (RSS); angle of arrival (AoA); maximum a posteriori (MAP) estimator; Kalman filter (KF)
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Tomic, S.; Beko, M.; Dinis, R.; Gomes, J.P. Target Tracking with Sensor Navigation Using Coupled RSS and AoA Measurements. Sensors 2017, 17, 2690.

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