The real-world applications in signal processing generally involve estimating the system
state or parameters in nonlinear, non-Gaussian dynamic systems. The estimation problem …

This article addresses the state-estimation problem for linear and non-linear systems for the
case in which prior knowledge is available in the form of an equality constraint. The equality …

This paper considers the state-estimation problem with a constraint on the data-injection
gain. Special cases of this problem include the enforcing of a linear equality constraint in the …

We present a robust null space method for linear equality constrained state space
estimation. Exploiting a degeneracy in the estimator statistics, an orthogonal factorization is …

The pseudo measurement method is a main approach to equality-constrained state
estimation due to its simplicity. It is, however, not popular due to possible numerical …

Environment perception is one of the major challenges in the vehicle industry nowadays, as
acknowledging the intentions of the surrounding traffic participants can profoundly decrease …

The state of many dynamic systems evolves subject to some equality constraints. Most
existing work focuses on developing state estimation algorithms for an equality-constrained …

This paper addresses the state-estimation problem for nonlinear systems with an interval
constraint on the state vector. Approximate solutions to this problem are reviewed and …

We provide a sensor fusion framework for solving the problem of joint ego-motion and road
geometry estimation. More specifically we employ a sensor fusion framework to make …

A distributed nonlinear estimation method based on soft-data-constrained multimodel
particle filtering and applicable to a number of distributed state estimation problems is …