A new tracker for air-to-air missile targets

Abstract

An extended Kalman filter is developed to aid the tracking of an air-to-air missile from a maneuvering target aircraft. The filter exploits knowledge of the dominant aerodynamically induced lift and drag forces of a nonthrusting missile employing proportional navigation guidance, and it also accounts for the dynamic lag and bandwidth effects of the missile seeker, guidance, and control systems. Incorporating the refined missile acceleration model enhances the filter's tracking estimate precision and provides meaningful threat predictive capabilities. Identifiability of parameters within the acceleration model is established, an adaptive filter is developed, and its performance capabilities portrayed through realistic Monte Carlo simulations.