Optimal guidance and nonlinear estimation for interception of decelerating targets

Optimal guidance and nonlinear estimation algorithms are formulated for the interception of a nonmaneuvering target vehicle decelerated by atmospheric drag. For an interceptor with two-axis control of translational acceleration, time-to-go may be selected to generate a zero-acceleration command along the uncontrolled axis. A nine-state, extended Kalman filter is formulated in relative-motion coordinates, and the target deceleration vector is modeled by a linear, tint-order process. 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. Theoretical collision probabilities are determined, using Monte Carlo simulations, as functions of sensor measurement accuracy, filter update rate, and engagement crossing angle. (Author)