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Nonlinear Recursive Filter for Boost Trajectories
2001 Award Winner
Michael E. Hough, The MITRE Corporation
ABSTRACT
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 dynamics model is
incorporated in an extended Kalman filter with nine state variables that describe the inertial
components of position, velocity and thrust acceleration. Additional algorithms are described for
filter initialization using angle-only measurements from a geostationary sensor and for detection
and estimation of the final staging event using measurement residuals. Tracking accuracy and
covariance fidelity are assessed by Monte-Carlo simulation.
Publication
Published in 2001. Informatica, Vol. 25, pp. 475-482.
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