Estimating Directional Data From Network Topology for Improving Tracking Performance
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Data
2019
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MDPI
Resumo
This work proposes a novel approach for tracking a moving target in non-line-of-sight
(NLOS) environments based on range estimates extracted from received signal strength (RSS) and
time of arrival (TOA) measurements. By exploiting the known architecture of reference points to act
as an improper antenna array and the range estimates, angle of arrival (AOA) of the signal emitted
by the target is first estimated at each reference point. We then show how to take advantage of these
angle estimates to convert the problem into a more convenient, polar space, where a linearization of
the measurement models is easily achieved. The derived linear model serves as the main building
block on top of which prior knowledge acquired during the movement of the target is incorporated
by adapting a Kalman filter (KF). The performance of the proposed approach was assessed through
computer simulations, which confirmed its effectiveness in combating the negative effect of NLOS
bias and superiority in comparison with its naive counterpart, which does not take prior knowledge
into consideration.
Descrição
Journal of Sensor and Actuator Networks
Palavras-chave
TARGET TRACKING, NON-LINE-OF-SIGHT, RECEIVED SIGNAL STRENGTH, TIME OF ARRIVAL, ANGLE OF ARRIVAL, KALMAN FILTER, ENGENHARIA ELETROTÉCNICA, ELECTROTECHNICAL ENGINEERING, TARGET TRACKING, FILTRO DE KALMAN, RECEIVED SIGNAL STRENGTH, ANGLE OF ARRIVAL, NON-LINE-OF-SIGHT, TIME OF ARRIVAL