Information, covariance and square-root filtering in the presence of unknown inputs
2007 European Control Conference (ECC), 2007The 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 +2 more
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Gain-free square root information filtering using the spectral decomposition
Journal of Guidance, Control, and Dynamics, 1989A new square root state estimation algorithm is introduced, that 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 exp T form, where V is the matrix whose columns are the eigenvectors of the ...
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The treatment of bias in the square-root information filter/smoother
Journal of Optimization Theory and Applications, 1973The 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.
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Applications of square-root information filtering and smoothing in spacecraft orbit determination
Proceedings of the 27th IEEE Conference on Decision and Control, 2003The JPL (Jet Propulsion Laboratory) orbit determination software system is a set of computer programs developed for the primary purpose of determining the flight path of deep-space mission spacecraft in NASA's planetary program and highly elliptical orbiting spacecraft in Earth orbit. The filtering processes available within the JPL orbit determination
null Tseng-Chan Wang +3 more
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Null-Space Square-Root Information Filtering and Smoothing for Singular Problems
Journal of Guidance, Control, and Dynamics, 2005A new algorithm that does square-root information filtering and fixed-interval smoothing has been developed for singular discrete-time estimation problems. Singular measurements arise if one uses a Markov measurement error model or if one uses the quaternion normalization constraint in an attitude determination problem.
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A multi-sensor tracking and identification algorithm using the square-root information filter
Proceedings of 32nd IEEE Conference on Decision and Control, 2002A multiple dissimilar sensor multi-target tracking and identification algorithm using the square-root information filter is proposed. The procedures employed within this algorithm minimize the computational effort by working entirely within the information domain and utilizing a coordinated approach to the treatment of both kinematic and non-kinematic ...
S. Bruder, R. Johnson, M. Farooq
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Square-root information filtering and smoothing for precision orbit determination
1982Square root information filtering and smoothing has, over the last few years, come to be recognized as a reliable and effective method for computing numerically accurate estimates in problems where high precision is required. Unfortunately, the algorithms employed often project an image of being too costly in terms of both computation and storage ...
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An application of the square-root information filter to large scale linear interconnected systems
IEEE Transactions on Automatic Control, 1977In this paper it is demonstrated that application of the square root information filter can dramatically reduce the storage and computation involved with estimation of certain classes of large scale interconnected systems.
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Implementing the square-root information Kalman filter on a Jacobi-type systolic array
Journal of VLSI signal processing systems for signal, image and video technology, 1994Several systolic Kalman filters have appeared in the literature, with often complex hardware constructs to accomodate the algorithmic `anomalies'. Here, we follow a different route by working the original information filter into a so-called `Jacobi-type' algorithm, which is much more regular and directly fits onto a common and general Jacobi-type ...
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