Nonlinear Recursive Filter for Boost Trajectories

A nonlinear recursive algorithm is formulated for state vector and covariance estimation of boost trajectories. The thrust acceleration vector of the booster is modeled by a vector-differential equation that includes effects of propellant depletion and attitude motions resulting from gravity-turn maneuvers and other steering maneuvers. This new dynamicsmodel is incorporated in an extended Kalman Ž lter with nine state variables that describe the inertial components of position, velocity, and thrust acceleration. Additional algorithms are described for Ž lter initialization using angle-only measurements from a geostationary sensor and for detection and estimation of the Ž nal staging event using measurement residuals. Tracking accuracy and covariance Ž delity are assessed byMonte Carlo simulation.