Trajectory Estimation of Reentry Vehicles by Use of On-Line Input Estimator

Trajectory estimation plays an important role in antitactical ballistic missile systems for tracking, guidance, and early warning. Model validation is a major challenge within the overall trajectory estimation problem. A novel on-line estimation approach in which an adaptive e lter is used to identify the trajectory of a reentry vehicle in the terminal phase from single-source-measured radar data is presented. The proposed approach consists of an extended Kalman e lter and an innovative recursive input estimator with an input detection. The model is formulated to identify an unmodeled acceleration input representing differences between the physical system and themathematicalmodel.Arecursiveleast-squaresestimatorisprovidedto extractthemagnitudeoftheunmodeled input and to offer a testing criterion for detection of the onset and the presence of the input. The estimated input is inserted into the extended Kalman e lter if the input is detected. Numerical simulation demonstrates superior capabilities as measured by accuracy and robustness of the proposed method. In real-e ight analysis, the adaptivee lteralso performsexceptionally well in termsofestimation and prediction.Therecommendedtrajectory estimation method can support defense and tactical operations for antitactical ballistic missile warfare.