Results 251 to 260 of about 17,529,102 (294)

Maximum Likelihood Estimation Using Square Root Information Filters

1989 American Control Conference, 1989
The maximum likelihood parameter estimation algorithm is known to provide optimal estimates for linear time-invariant dynamic systems. However, the algorithm is computationally expensive and requires evaluations of the gradient of a log likelihood function and the Fisher information matrix.
G.J. Bierman, M.R. Belzer, J.S. Vandergraft, D.W. Porter   +3 more
openaire   +1 more source

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.
Michel Vanbegin, Paul Van Dooren, Michel Verhaegen   +2 more
openaire   +1 more source

Systolic approach to square root information Kalman filtering

International Journal of Control, 1989
The systolic approach to Kalman filtering is described, which reduces an algorithm to its computational components which can then be mapped onto a parallel processing array. Square root information processing is considered, and two new algorithms are derived from a least-squares viewpoint and are shown to be equivalent to the Kalman filter.
F. M. F. GASTON, G. W. IRWIN
openaire   +1 more source

Information, covariance and square-root filtering in the presence of unknown inputs

2007 European Control Conference (ECC), 2007
The optimal filtering problem for linear systems with unknown inputs is addressed. Based on recursive least-squares estimation, information formulas for joint input and state estimation are derived. By establishing duality relations to the Kalman filter equations, covariance and square-root forms of the formulas follow almost instantaneously.
Steven Gillijns, Niels Haverbeke, Bart De Moor   +2 more
openaire   +1 more source

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 ...
openaire   +1 more source

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
openaire   +1 more source

Two-stage information filters for single and multiple sensors, and their square-root versions

Automatica, 2018
Accurate states and unknown random bias estimation for well- and ill-conditioned systems are crucial for several applications. In this paper, a fusion of a two-stage Kalman filter and an information filter, and its extensions are considered to estimate the state variables and unknown random bias.
Chandra, Kumar Pajkki Bharani, Darouach, Mohamed   +1 more
openaire   +1 more source

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
openaire   +1 more source

The treatment of bias in the square-root information filter/smoother

Journal of Optimization Theory and Applications, 1973
The Dyer-McReynolds square-root information filter (SRIF) is rederived, using recursive least-square arguments. The result is applied to a system composed partly of biases. The filter sensitivity matrix, computed covariance, and consider covariance for this augmented system are reviewed.
openaire   +1 more source

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.
Du Yong Kim, Moongu Jeon
openaire   +3 more sources