Precise Reentry Maneuver Estimation Using Radar Trilateration

作     者：Hough, Michael E. 

作者机构：Raytheon Co 235 Presidential Way Woburn MA 01801 USA 

出 版 物：《JOURNAL OF GUIDANCE CONTROL AND DYNAMICS》 (制导、控制和动力学杂志)

年 卷 期：2020年第43卷第3期

页      面：422-437页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 08[工学] 0804[工学-仪器科学与技术] 0825[工学-航空宇航科学与技术] 

主　　题：RADAR Dynamic Pressure Probability Density Functions Recursive Filter Monte Carlo Simulation Lift Coefficient Earth Aerodynamic Coefficients Extended Kalman Filter Guidance Algorithms 

摘      要：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.