An iterated recursive filter is formulated for radar trilateration of reentry maneuvers. Using range and range rate measurements from three radars in a regional network, trilateration provides very accurate three-dimensional position and velocity measurements, which improves drag and lift acceleration estimates. A new first-order, nonlinear vector differential equation specifies the rate of change of acceleration (or jerk). Acceleration process noise is determined from dynamic pressure estimates and mean-square area-to-mass covariances, which are derived from probability density functions that statistically characterize a family of expected maneuvers. Trilateration accuracies are demonstrated for demanding reentry maneuvers. Monte Carlo simulations assess accuracy sensitivity to modeling assumptions and to off-nominal reentry trajectories.
Precise Reentry Maneuver Estimation Using Radar Trilateration
Journal of Guidance, Control, and Dynamics ; 43 , 3 ; 422-437
2019-10-29
16 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Reentry Maneuver Estimation Using Nonlinear Markov Acceleration Models
Online Contents | 2017
|Reentry Maneuver Estimation Using Nonlinear Markov Acceleration Models
Online Contents | 2017
|Reentry Maneuver Estimation Using Nonlinear Markov Acceleration Models
Online Contents | 2017
|