Results 121 to 130 of about 68,495 (163)

Square root unscented information filter for multiple model estimation

TENCON 2015 - 2015 IEEE Region 10 Conference, 2015
This paper proposes a new multiple model estimation method which employs the square root version of unscented information filter (SRUIF) in the framework of interacting multiple model (IMM). Comparing with the general UIF, the square root version has better numerical characteristics, such as improved numerical accuracy, double order precision and ...
Guoliang Liu, null Guohui Tian
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Square-Root Extended Information Filter for Visual-Inertial Odometry for Planetary Landing

Journal of Guidance, Control, and Dynamics, 2023
A novel sequential information filter formulation for computationally efficient visual-inertial odometry and mapping is developed in this work and applied to a realistic moon landing scenario. Careful construction of the square-root information matrix, in contrast to the full information or covariance matrix, provides easy and exact mean and ...
Matthew W. Givens, Jay W. McMahon
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Square-root information filter based sensor data fusion algorithm

Proceedings of IEEE International Conference on Industrial Technology 2000 (IEEE Cat. No.00TH8482), 2005
In this paper the square-root information filter is studied for possible application to sensor data fusion process. Sensor data fusion is gaining increasing importance in modern technologies. The merit of the information fusion approach is that the fusion at measurement level is quite straightforward.
J.R. Raol, G. Girija
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Algorithm 675: Fortran subroutines for computing the square root covariance filter and square root information filter in dense or Hessenberg forms

ACM Transactions on Mathematical Software, 1989
In this paper, codes are provided for two of the most popular square root filters: the Square Root Covariance Filter and the Square Root Information Filter. We also give efficient implementations for the time invariant case based on so-called condensed forms. All routines make extensive use of BLAS routines.
Vanbegin, Michel, Van Dooren, Paul, Verhaegen, Michel   +2 more
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Square root information filtering using the covariance spectral decomposition

Proceedings of the 27th IEEE Conference on Decision and Control, 2003
A square-root state-estimation algorithm is introduced which operates in the information mode in both the time and the measurement update stages. The algorithm, called the V-Lambda filter, is based on the spectral decomposition of the covariance matrix into a V Lambda V/sup T/ form, where V is the matrix whose columns are the eigenvectors of the ...
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On the application of discrete square-root information filtering†

International Journal of Control, 1974
Properties of the Householder transformation and its application to square-root information filtering (SRIF) are reviewed. The Householder algorithm is used to arrive at an improved SRIF mechanization for the case of coloured noise. It is also used to construct an error analysis algorithm which accounts for the use of incorrect a priori statistics in ...
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Square Root Quadrature Information Filters for Multiple Sensor Fusion

2018
This paper presents new algorithms for square root quadrature information filers which are intended for multiple sensor fusion. The use of recently proposed quadrature rules for numerical approximation of Bayesian integrals enables these filters to demonstrate improved estimation accuracy over their competing algorithms.
Aritro Dey, Smita Sadhu, Tapan Kumar Ghoshal   +2 more
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Generalized Square-Root Information Consider Covariance Analysis for Filters and Smoothers

Journal of Guidance, Control, and Dynamics, 2013
A new form of consider covariance analysis for studying incorrectly modeled square-root information filters and smoothers is presented and demonstrated. The value of this technique is its ability to compute the true estimation error covariance when the estimator has an incorrect dynamic model, an incorrect measurement model, or an incorrect statistical
Joanna C. Hinks, Mark L. Psiaki
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Square Root Receding Horizon Information Filters for Nonlinear Dynamic System Models

IEEE Transactions on Automatic Control, 2013
New nonlinear filtering algorithms are designed based on a receding horizon strategy, i.e., a finite impulse response (FIR) structure, and square root information filtering to achieve high accuracy and good performance in empirical error covariance tests.
Kim, Du Yong, Jeon, M.
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Square-root information-type methods for continuous–discrete extended Kalman filtering

European Journal of Control
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Maria V. Kulikova, Gennady Yu. Kulikov
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