|TDOA/FDOA based Target Tracking with Imperfect Position and Velocity Data of Distributed Moving Sensors
Seul-Ki Han, Won-Sang Ra, and Jin Bae Park
International Journal of Control, Automation, and Systems, vol. 15, no. 3, pp.1155-1166, 2017
Abstract : "This paper addresses the target tracking problem using time difference of arrival (TDOA) and frequency
difference of arrival (FDOA) measured by moving sensor network whose position and velocity are noise contaminated.
It is a known fact that the existing approaches to this problem still have two unsolved technical issues; the
unsatisfactory convergence behavior of the tracking filter mainly caused by severe nonlinearity of the problem itself
and the tracking performance degradation due to the sensor position and velocity errors. In order to resolve these
matters radically, the given target tracking problem is formulated as the robust state estimation problem of the linear
system with stochastic uncertainties in its measurement matrix and solved by using the robust Kalman filter theory.
The proposed scheme enables us to overcome the inherent limitations of the conventional nonlinear filters for its
linear filter structure. It can also prevent the performance degradation due to imperfect sensor position and velocity
information. Through the simulations, the effectiveness and reliable target tracking performance of the proposed
method are demonstrated."
Kalman filter, state estimation, target tracking, moving sensor network, uncertain systems.
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