State estimation under nonlinear state inequality constraints. A tracking application
Vincent Sircoulomb, Ghaleb Hoblos, Houcine Chafouk, José Ragot · 2008
This paper proposes a general method for dealing with state estimation under nonlinear state soft inequality constraints. This method is based on the projection approach, and then has the advantage to be compatible with any kind of state estimator. In order to be taken into account, the nonlinear constraints are linearized about the constrained state using an iterated approach. The proposed algorithm is tested on a three- dimension tracking application with nonlinear constraints on the moving body acceleration. The results are compared with those of an unconstrained Kalman filter.