Air-to-Air Missile Enhanced Scoring with Kalman Smoothing

A correct estimate of a missile\u27s flight path is essential to USAF test and evaluation efforts. The USAF air-to-air Weapons System Evaluation Program (WSEP) targets unmanned aerial drones in hundreds of live-fire missile tests each year. The current QF-4 drone inventory is expected to be depleted by 2015. The QF-16 Full Scale Aerial Target (FSAT) contract has been awarded to convert usable early model F-16s into remote-controlled drones. The QF-16 will provide a highly-maneuverable, realistic testing environment for 5th generation fighters. To accomplish their mission, WSEP requires a scoring system capable of estimating the trajectory of a missile relative to the drone aircraft. When a missile fails to destroy a target aircraft, this scoring system is useful in analyzing whether a missile suffered a guidance failure, decoyed on aircraft countermeasures, or lacked energy or maneuverability to complete the intercept. Missile flight path reconstruction near the drone allows evaluation of the missile\u27s performance. Estimating the trajectory of an air-to-air missile provides many unique challenges. This is complicated by the high velocities and extremely high turn rates attained by the missile during its short Time-of-Flight (TOF) en route to the target. Kalman smoothers lend themselves to tasks such as post-flight trajectory estimation because they combine the utility of forward and backward-propagating Kalman filters. The combined result is maximum accuracy for post-flight missile scoring. Six Kalman smoothers (EKS, IEKS, SFRA EKS, UKS, IUKS, and SFRA UKS) are simulated. The performance assessment is based on multiple Monte Carlo comparisons among all algorithms with a variety of missile models and air-to-air engagement scenarios. This technical assessment provides the basis for recommendation of the Unscented Kalman Smoother (UKS) as the DoD/USAF standard for post-processing and scoring live-fire missile data