Optimal guidance and nonlinear estimation for interception of decelerating targets
Michael E. Hough · Journal of Guidance Control and Dynamics · 1995
Optimal guidance and nonlinear estimation algorithms are formulated for interception of an accelerating target vehicle during boost. For an interceptor with two-axis control of translational acceleration, time to go may be selected to null the component of commanded acceleration along the uncontrolled axis. A nine-state, extended Kalman filter is formulated, in a Cartesian-inertial frame. The filter dynamics model includes a vector-differential equation for the thrust acceleration vector of the target during a gravity-turn maneuver. With angle measurements from a strapdown seeker, very small miss distances can be achieved, despite large estimation errors in range, because of the time-to-go algorithm. Monte Carlo simulations are used to generate theoretical collision probabilities as functions of sensor measurement accuracy and filter update rate.