Mar 2, 2021 · A criterion that acts as a guideline for a reasonable choice of the step size is proposed. This criterion is based on the predictor-corrector error covariance ...
Abstract—In Kalman filtering (KF), a tradeoff exists when selecting the filter step size. Generally, a smaller step size improves the estimation accuracy, ...
Dec 9, 2024 · In Kalman filtering, a trade-off exists when selecting the filter step size. Generally, a smaller step size improves the estimation accuracy ...
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The Kalman filter requires knowledge of the noise statistics; however, the noise covariances are generally unknown. Although this problem has a long history ...
Adaptive cubature Kalman filter based on the variance-covariance ...
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Mar 9, 2017 · Although the Kalman filter (KF) is widely used in practice, its estimated results are optimal only when the system model is linear and the ...
This article addresses the subject of making a choice between the adaptive and robust methods when abnormal innovation occurs.
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Aug 23, 2016 · In the proposed adaptive algorithm, the process noise covariance is computed using the real-time information of the innovation sequence.
In statistics and control theory, Kalman filtering is an algorithm that uses a series of measurements observed over time, including statistical noise and ...
We present an optimization criterion and a novel six-step approach based on a successive approximation, coupled with a gradient algorithm with adaptive step ...
A resolution is proposed to directly estimate or tune the process noise covariance matrix in Kalman filtering using variational Bayesian technique.
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