THE well-known Kalman filter is an optimal unbiased estimator for linear dynamic systems
with Gaussian noise and non-Gaussian noise ([1] p. 480). In a number of practical situations …

STATE estimation is of great practical importance. For instance, output feedback control
systems often consist of a state feedback control law with the states replaced by state …

IN MANYengineering applications, knowledge of a system's state is needed. Because states
are rarely measured directly, the states are usually estimated using noise corrupted …

The problem of estimating the state vector of a dynamical system from vector measurements
when it is known that the state vector satisfies norm equality constraints is considered. The …

A new method is presented for optimally enforcing an algebraic constraint in Kalman
filtering. The method is illustrated in the setting of inertial navigation using extended Kalman …

This article is concerned with the state estimation problem for linear systems with linear state
equality constraints. We re-examine constrained Kalman filter variations and propose an …

An analytic method was developed by D. Simon and TL Chia to incorporate linear state
equality constraints into the Kalman filter. When the state constraint was nonlinear …

This paper considers continuous-time state estimation when part of the state estimate or the
entire state estimate is norm-constrained. In the former case continuous-time state …

Redundant attitude representations are often used in Kalman filters for estimating dynamic
states that include an attitude. A minimal three-element attitude deviation is combined with a …

Efficient square root algorithm for measurement update in Kalman filtering Page 1 VOL. 6, NO.
3 J. GUIDANCE MAY-JUNE 1983 Efficient Square Root Algorithm for Measurement Update in …