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- W2227189186 abstract "Moving objects tracking is an active problem in computer vision and has a wide variety of applications. The Kalman Filter algorithm has been commonly used for estimation and prediction of the target position in target tracking domain, of which the algorithm is adaptive to linear system, but the error of Kalman Filter will become large or even diverging when the target status changes suddenly. In this paper, multi-innovation theory is applied to target tracking, and the Multi-innovation Kalman Filter is proposed. Multi-innovation Kalman Filter has better precision and stability, because Multi-innovation Kalman Filter takes not only the moving targets’ current state of motion into consideration, but also the time before. In addition, the authors theoretically analyzed the convergence of improved Multi-innovation Kalman Filter algorithm. Finally, simulation results show that the improved algorithm Multi- innovation Kalman Filter is superior to the traditional Kalman Filter." @default.
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- W2227189186 date "2015-01-01" @default.
- W2227189186 modified "2023-09-27" @default.
- W2227189186 title "Research and Application of Moving Target Tracking Based on Multi-innovation Kalman Filter Algorithm" @default.
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- W2227189186 doi "https://doi.org/10.1007/978-3-662-48570-5_10" @default.
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