Maneuvering target interception using retrospective-cost-based adaptive input and state estimation

Abstract

In this paper, missile guided by modified proportional navigation guidance (MPNG) law intercepts the maneuvering target using estimated target acceleration. Target acceleration is taken as an input and is estimated with retrospective cost-based-adaptive input and state estimation (RCAISE). Prior optimized input estimates are used in the adaptive input estimator, which is based on the recursive least squares, to estimate the unknown input acceleration of the maneuvering target. Kalman filter uses the estimated input acceleration of the target to estimates the states of the maneuvering target. MPNG law uses the estimated input acceleration of the target to intercept the maneuvering target. Numerical simulation results present herein, demonstrate better performance of the RCAISE as compare to other classical estimation methods.