Results 21 to 30 of about 623,679 (298)
Proceedings of the National Academy of Sciences, 2001 The Kalman Filter commonly employed by control engineers and other physical scientists has been successfully used in such diverse areas as the processing of signals in aerospace tracking and underwater sonar, and statistical quality control.
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IEEE Transactions on Automatic Control, 2009 In this paper, we present a new nonlinear filter for high-dimensional state estimation, which we have named the cubature Kalman filter (CKF). The heart of the CKF is a spherical-radial cubature rule, which makes it possible to numerically compute multivariate moment integrals encountered in the nonlinear Bayesian filter. Specifically, we derive a third-
Ienkaran Arasaratnam, Simon Haykin 0001
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Auto‐calibration Kalman filters for non‐linear systems with direct feedthrough
IET Control Theory & Applications, 2021 The problem of state estimation for non‐linear systems with unknown inputs is discussed. The objective is to construct a non‐linear filter where the unknown input affects both the state equation and measurement equation. An auto‐calibration Kalman filter
Yi Cui, Zhihua Wang
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Remote Sensing, 2021 The extended Kalman filter is an extended version of the Kalman filter for a non-linear problem. This study applies this extended Kalman filter to the real-time estimation of the parameters of the dual-pol radar rain rate estimator.
Wooyoung Na, Chulsang Yoo
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Kalman interpolation filter for channel estimation of LTE downlink in high-mobility environments [PDF]
, 2012 The estimation of fast-fading LTE downlink channels in high-speed applications of LTE advanced is investigated in this article. In order to adequately track the fast time-varying channel response, an adaptive channel estimation and interpolation ...
Dai, Xuewu +14 more
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A review: state estimation based on hybrid models of Kalman filter and neural network
Systems Science & Control Engineering, 2023 In this paper, hybrid models of Kalman filter and neural network for state estimation are reviewed of their corresponding academic achievements, the creation of which is a noteworthy development in state estimation.
Shuo Feng +5 more
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CoRR, 2021 The Kalman filter is a fundamental filtering algorithm that fuses noisy sensory data, a previous state estimate, and a dynamics model to produce a principled estimate of the current state. It assumes, and is optimal for, linear models and white Gaussian noise. Due to its relative simplicity and general effectiveness, the Kalman filter is widely used in
Beren Millidge +3 more
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A parallel Kalman filter via the square root Kalman filtering [PDF]
, 1993 A parallel algorithm for Kalman filtering with contaminated observations is developed. Theı parallel implementation is based on the square root version of the Kalman filter (see [3]).
Romera, Rosario, Cipra, Tomas
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Multiplicative Kalman filtering [PDF]
TEST, 2010 We study a non-linear hidden Markov model, where the process of interest is the absolute value of a discretely observed Ornstein-Uhlenbeck diffusion, which is observed after a multiplicative perturbation. We obtain explicit formulae for the recursive relations which link the relevant conditional distributions.
Comte, Fabienne +2 more
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Robust adaptive estimators for nonlinear systems [PDF]
, 2013 This paper is concerned with the development of new adaptive nonlinear estimators which incorporate adaptive estimation techniques for system noise statistics with the robust technique.
Katebi, Reza +1 more
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