Results 231 to 240 of about 12,338 (264)

Invariant Kalman Filtering

Annual Review of Control, Robotics, and Autonomous Systems, 2018
The Kalman filter—or, more precisely, the extended Kalman filter (EKF)—is a fundamental engineering tool that is pervasively used in control and robotics and for various estimation tasks in autonomous systems. The recently developed field of invariant extended Kalman filtering uses the geometric structure of the state space and the dynamics to improve
Bonnabel, Silvere, Barrau, Axel
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Fuzzy Kalman filtering

Information Sciences, 1998
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Guanrong Chen, Qingxian Xie, Leang-San Shieh   +2 more
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Kalman filter and quantization

Problems of Information Transmission, 2007
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Quantized Kalman Filtering

2007 IEEE 22nd International Symposium on Intelligent Control, 2007
This paper is concerned with the estimation problem for a dynamic stochastic estimation in a sensor network. Firstly, the quantized Kalman filter based on the quantized observations (QKFQO) is presented. Approximate solutions for two optimal bandwidth scheduling problems are given, where the tradeoff between the number of quantization levels or the ...
Shuli Sun, Jianyong Lin, Lihua Xie 0001, Wendong Xiao   +3 more
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Klassisches Kalman-Filter

2017
Damit Kalman-Filter korrekt eingesetzt werden konnen, ist es wichtig, die Randbedingen zu kennen, unter der die Kalman-Gleichungen verwendet werden durfen. Dies bedeutet, dass die jeweilig zu losende Aufgabe dahingehend zu uberprufen ist. Sind diese Voraussetzungen nicht gegeben, liefern die Kalman-Gleichungen nicht das gewunschte Ergebnis.
Reiner Marchthaler, Sebastian Dingler
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Kalman filtering revisited

Proceedings of the 2000 American Control Conference. ACC (IEEE Cat. No.00CH36334), 2000
Infinite-horizon Kalman filtering is re-examined and generalized to include a class of nonstationary and nonergodic disturbances. This revision is achieved by defining a generalized infinite-horizon filtering problem using a flexible functional analytic signal description. It is shown that the solution to the generalized filtering problem is equivalent
Pertti M. Makila, J. Paattilammi
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Modified Kalman filtering

IEEE Transactions on Signal Processing, 1994
A modified Kalman filtering algorithm is described. The key point of the new algorithm is a model mismatch function, which accounts for deviation of the model from the ideal condition of orthogonality between the innovations process and past observations. >
Simon Haykin 0001, Liang Li
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State-Space Model and Kalman Filter Gain Identification by a Kalman Filter of a Kalman Filter

Journal of Dynamic Systems, Measurement, and Control, 2017
This paper describes an algorithm that identifies a state-space model and an associated steady-state Kalman filter gain from noise-corrupted input–output data. The model structure involves two Kalman filters where a second Kalman filter accounts for the error in the estimated residual of the first Kalman filter.
Minh Q. Phan, Francesco Vicario, Richard W. Longman, Raimondo Betti   +3 more
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Kalman filter and extended Kalman filter

2017
In the Bachelor’s thesis we describe the Kalman filtering algorithm for linear-Gaussian state space models and give an example of its application. We describe the extended Kalman filter for differentiable Gaussian state space models and give examples of its application.
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Fractional Kalman filters

Automatica
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Xusheng Yang, Wen-An Zhang 0001, Li Yu 0001   +2 more
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