Uncertainty Exchange Through Multiple Quadrature Kalman Filtering.
IEEE Signal Processing Letters(2016)
摘要
One of the major challenges in Bayesian filtering is the curse of dimensionality. The quadrature Kalman filter (QKF) is the method of choice in many real-life Gaussian problems, but its computational complexity increases exponentially with the dimension of the state. As a promising solution to overcome the filter limitations in such scenarios, we further explore the multiple state-partitioning app...
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关键词
Uncertainty,Kalman filters,Bayes methods,Target tracking,Computational complexity,Robustness,Time measurement
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