Next-Generation Target State Estimation Algorithms for the Interception of Maneuvering Ballistic Missiles

Ballistic target interception requires extremely high accuracy with a sub-meter level miss distance due to the need to achieve kinetic kill. Since the task is even more challenging when the target performs unpredictable maneuvers, highly accurate state estimators are indispensable for successful ballistic target interception. The proposed research will employ a nonlinear dynamic model capable of reproducing a wide variety of target motions, including intelligent evasive maneuvers for estimator development. A realistic seeker model including non-Gaussian noise sources will be included in the formulation. Advanced estimation techniques such as the particle filter and its variations will be considered to deal with highly nonlinear/non-Gaussian system properties induced by the seeker sensor model and nonlinear state/parameter filter dynamics. Phase I research will develop an advanced filtering algorithm along with the formulation of a realistic seeker sensor model, and demonstrate the feasibility of the proposed online estimation strategy to be applied to the tracking of a maneuvering ballistic target. Phase II research will expand on the estimation strategy and its simulation software implementation developed during the Phase I. More emphasis will be put on the integrated interception strategy including guidance and control during the Phase II.