Application of Extended Kalman Filter to Tactical Ballistic Missile Re-entry Problem

TL;DR

This paper explores the use of the Extended Kalman Filter to improve position and velocity estimation during the non-linear re-entry phase of tactical ballistic missiles, demonstrating enhanced accuracy with higher ballistic coefficients.

Contribution

It applies and evaluates the Extended Kalman Filter specifically for missile re-entry estimation, highlighting its advantages over traditional methods in this context.

Findings

Better estimation accuracy with increased ballistic coefficient

Effective non-linear system estimation using EKF

Improved tracking performance in missile re-entry scenarios

Abstract

The objective is to investigate the advantages and performance of Extended Kalman Filter for the estimation of non-linear system where linearization takes place about a trajectory that was continually updated with the state estimates resulting from the measurement. Here tactile ballistic missile Re-entry problem is taken as a nonlinear system model and Extended Kalman Filter technique is used to estimate the positions and velocities at the X and Y direction at different values of ballistic coefficients. The result shows that the method gives better estimation with the increase of ballistic coefficient.