Aim Identification of Missiles with a Minimal Parameter Set

Considered here is 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 or not. A mathematical model is presented for a missile under pure proportional navigation (PPN) with a changing velocity (direction change as well as speed change), to intercept a nonmaneuvering aircraft. A maximum likelihood (ML) estimator 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 such as a genetic algorithm (GA) 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.