Results 21 to 30 of about 1,778,758 (298)
Adaptive Kalman filtering [PDF]
Analytical Chemistry, 1991 The increased power of small computers makes the use of parameter estimation methods attractive. Such methods have a number of uses in analytical chemistry. When valid models are available, many methods work well, but when models used in the estimation are in error, most methods fail.
Sarah C. Rutan, Steven D. Brown
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Filtering performance analyizing for Relative Navigation using Single Difference Carrier-Phase GPS [PDF]
Journal of Astronomy and Space Sciences, 2008 Satellite formation flying can provide the platform for interferometric observation to acquire the precise data and ensure the flexibility for space mission.
In-Kwan Park +4 more
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An exact minimum variance filter for a class of discrete time systems with random parameter perturbations [PDF]
, 2014 An exact, closed-form minimum variance filter is designed for a class of discrete time uncertain systems which allows for both multiplicative and additive noise sources.
Anderson +24 more
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A Localization Based on Unscented Kalman Filter and Particle Filter Localization Algorithms
IEEE Access, 2020 Localization plays an important role in the field of Wireless Sensor Networks (WSNs) and robotics. Currently, localization is a very vibrant scientific research field with many potential applications.
Inam Ullah +4 more
semanticscholar +1 more source
Italian National Conference on Sensors, 2020 Detection and distance measurement using sensors is not always accurate. Sensor fusion makes up for this shortcoming by reducing inaccuracies. This study, therefore, proposes an extended Kalman filter (EKF) that reflects the distance characteristics of ...
Taek-Lim Kim, Tae-Hyoung Park
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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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A Neuron-Based Kalman Filter with Nonlinear Autoregressive Model
Italian National Conference on Sensors, 2020 The control effect of various intelligent terminals is affected by the data sensing precision. The filtering method has been the typical soft computing method used to promote the sensing level. Due to the difficult recognition of the practical system and
Yu-ting Bai +4 more
semanticscholar +1 more source
Journal of Statistical Software, 2011 Support in R for state space estimation via Kalman filtering was limited to one package, until fairly recently. In the last five years, the situation has changed with no less than four additional packages offering general implementations of the Kalman filter, including in some cases smoothing, simulation smoothing and other functionality.
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Minimum Error Entropy Kalman Filter [PDF]
IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2019 To date, most linear and nonlinear Kalman filters (KFs) have been developed under the Gaussian assumption and the well-known minimum mean square error (MMSE) criterion.
Badong Chen +4 more
semanticscholar +1 more source