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Missile motion parameter estimation with a passive sensor from a high speed aircraft

The 3D trajectory estimation and observability problems of a target have been solved by using angle-only measurements. In previous works, the measurements were obtained in the thrusting/ballistic phase from a single fixed passive sensor. The present work solves the motion parameter estimation of a ballistic target in the reentry phase from a moving passive sensor on a fast aircraft. This is done with a 7-dimension motion parameter vector (velocity azimuth angle, velocity elevation angle, drag coefficient, target speed and 3D position). The maximum likelihood (ML) estimator is used for the motion parameter estimation at the end of the observation interval. Then we can predict the future position at an arbitrary time and the impact point of the target. The observability of the system is verified numerically via the invertibility of the Fisher information matrix. The Cramer–Rao lower bound for the estimated parameter vector is evaluated, and it shows that the estimates are statistically efficient. Simulation results show complete observability from the scenario considered, which illustrates that a single fast moving sensor platform for a target can estimate the motion parameter in the reentry phase.