Aim Identification with a Minimal Parameter Set

This paper considers the problem of using passive (line-of-sight angle) observations of a surface to air or an air to air missile (pursuer) from an aircraft (evader), to infer whether the missile is or is not aimed at the aircraft. The observations are assumed to be made only on an initial portion of the pursuer's trajectory. The approach is to model the trajectory of the missile with a number of kinematic and guidance parameters, estimate them and use statistical tools to infer whether the missile is guided toward the aircraft. A mathematical model is presented for a missile under pure proportional navigation with a changing velocity (direction change as well as speed change), to intercept a nonma-neuvering aircraft. A maximum likelihood estimator (MLE) is used for estimating the missile's motion parameters and a goodness-of-fit test is formulated to test if the aircraft is the aim or not. Using measurement data from several realistic missiles aimed at an aircraft, it is shown that the proposed method can solve this problem successfully. The key to the solution, in addition to the missile model parametrization, is the use of a reliable global optimization algorithm for the MLE. The estimation/decision algorithm presented here can be used for an aircraft to decide, in a timely manner, whether appropriate countermeasures are necessary.