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• W3159787776 abstract "This paper peruses the Doppler-bearing passive target tracking (DBT), a task that is subject to the nonlinear measurement equations. These measurement equations form the target tracking a nontrivial duty. In order to defeat these problems, many studies have reported various nonlinear estimation techniques, such as sigma-point Kalman filters. These types of filters have demonstrated superior performances for nonlinear system parameter estimation. Consequently, the main contribution of this paper is to improve the performance of the sigma-point Kalman filters. Thereafter, this paper introduces a transformed unscented simplex cubature Kalman filter, in which adaptation techniques are utilized to reduce the dependency of the proposed filter performance on the priori statistical information of the process and measurement noises. Moreover, the proposed filter is initialized by the range-parameterised Unscented Kalman filter. The Cramér–Rao lower bound (CRLB) determines the best accessible accuracy of estimators, which is utilized in this paper to accredit the performance of the proposed filter. The validity and feasibility of the proposed filter are confirmed by Monte Carlo simulations." @default.
• W3159787776 created "2021-05-10" @default.
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• W3159787776 date "2021-05-04" @default.
• W3159787776 modified "2023-09-27" @default.
• W3159787776 title "Adaptive Transformed Unscented Simplex Cubature Kalman Filter for Target Tracking" @default.
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• W3159787776 doi "https://doi.org/10.1080/03772063.2021.1919223" @default.
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