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For the over-the-horizon radar (OTHR) based target tracking, the reflecting height of the ionosphere, which reflects radar signals, is important. Existing methods assume that this height is exactly known a priori. In practice, however, we can only determine its range, not its specific value. To circumvent this problem, we propose to use a multiple-model approach in which each model corresponds to...
For extended-object/group-target tracking (EOT/GTT), the random-matrix approach is appealing. This approach assumes that the measurements are linear in the state and in the noise with its covariance being a random matrix to represent the object extension or the target group. In practice, however, the measurements are nonlinear in the state and noise. This paper proposes a random-matrix approach for...
In joint tracking and classification (JTC) problems, both decision and estimation are involved and they affect each other. Good solutions for JTC require solving the two problems jointly. A joint decision and estimation (JDE) framework based on a generalized Bayes risk was recently proposed for solving the problem of inter-dependent decision and estimation. In the JDE framework, a conditional JDE...
When tracking with multiple radars or sonars in Cartesian coordinates, the errors of converted measurements are correlated across radar or sonar stations due to their dependency on the state. In this paper, this cross-correlation is fully considered and a closed form of the cross-covariance across radars or sonars is presented for both 2D and 3D Cartesian coordinates. Two relative estimation performance...
The measurement model nonlinearity is a major challenge in target tracking. This paper presents a comparative performance study of seven nonlinear filters in handling the measurement model nonlinearity. They are: the extended Kalman filter, the unscented filter, the second order divided-differences filter, the Gauss-Hermite quadrature filter, the two-step Kalman filter, the Gaussian particle filter,...
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