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25 September 2007 Robust tracking for very long range radars: Part I. Algorithm comparisons
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The problem of tracking with very long range radars is studied in this paper. An important feature of the measurement conversion from a radar's r-u-v coordinate system to the Cartesian coordinate system is that, beyond a certain limit, measurement conversion based on the second order Taylor expansion (CM2) is necessary (and sufficient) to guarantee the consistency of the converted measurements (see part II [1] for the details). Initialized with the converted measurements (using CM2), four Cartesian filters are evaluated. It is shown that, among these filters, the Converted Measurement Kalman Filter with second order Taylor expansion (CM2KF) is the only one that is consistent for very long range tracking scenarios. Another two approaches, the Range-Direction-Cosine Extended Kalman Filter (ruvEKF) and the Unscented Kalman Filter (UKF) are also evaluated and shown to suffer from consistency problems. However, the CM2KF has the disadvantage of reduced accuracy in the range direction. To fix this problem, a consistency-based modification for the standard Extended Kalman Filter (E1KF) is proposed. This leads to a new filtering approach, designated as Measurement Covariance Adaptive Extended Kalman Filter (MCAEKF). For very long range tracking scenarios, the MCAEKF is shown to produce consistent filtering results and be able to avoid the loss of accuracy in the range direction. It is also shown that the MCAEKF meets the Posterior Carmer-Rao Lower Bound for the scenarios considered.
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X. Tian and Y. Bar-Shalom "Robust tracking for very long range radars: Part I. Algorithm comparisons", Proc. SPIE 6699, Signal and Data Processing of Small Targets 2007, 66990G (25 September 2007);

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