Factorization Methods for Discrete Sequential Estimation (Dover Books on Mathematics)

Factorization Methods for Discrete Sequential Estimation (Dover Books on Mathematics)

<DIV>This estimation reference text thoroughly describes matrix factorization methods successfully employed by numerical analysts, familiarizing readers with the techniques that lead to efficient, economical, reliable, and flexible estimation algorithms.<br>Topics include a review of least squares data processing and the Kalman filter algorithm; positive definite matrices, the Cholesky decomposition, and some of their applications; Householder orthogonal transformations; sequential square root data processing; mapping effects and process noise; biases and correlated process noise; and covariance analysis of effects due to mismodeled variables and incorrect filter <I>a priori</I> statistics. The concluding chapters explore SRIF error analysis of effects due to mismodeled variables and incorrect filter <I>a priori </I>statistics as well as square root information smoothing. Geared toward advanced undergraduates and graduate students, this pragmatically oriented and detailed presentation is also a useful reference, featuring numerous helpful appendixes throughout the text.</DIV>