Estimation and Interception of a Spiralling Target on Reentry in the Presence of non-Gaussian Measurement Noise

Abstract

This work addresses the problem of tracking and interception of a ballistic target having spiralling motion on re-entry. Interception is achieved by an interceptor missile which collects the required measurements using an inbuilt seeker, such that accurate estimates for target states are generated. The usual assumption that these measurements are corrupted by Gaussian noise is revisited, as significant outliers are observed in radar measurements. Since the conventional estimators tend to diverge in the presence of measurement outliers, this work propose an accurate and robust estimation algorithm by incorporating the maximum correntropy (MC) criterion. Hence, a Cauchy kernel based MC unscented Kalman filter (CM-UKF) is proposed for accurate state estimation. Also, proportional navigation guidance (PNG) law is implemented such that a possible interception is realized. The estimation accuracy of CM-UKF along with the PNG law is compared with that of the traditional UKF and Gaussian kernel based MC UKF (MC-UKF), by evaluating the average miss-distance and root mean square error (RMSE) in states.