Estimation of singularities for intercept point forecasting

In this paper, a recursive approach (an algorithm for estimation of singularity (AES)) is proposed to forecast the intercept point of a target and the pursuing interceptor recognized as the estimated singularity of a nodal cubic curve fitted to the data. The data comprises direction of arrival (DOA) estimates of both target and interceptor obtained at regular intervals of time using the maximum likelihood (ML) DOA estimation method. The estimates of coefficients of the cubic polynomial are given by a recursive least squares solution. From these coefficients, closed-form solutions for angle of interception and intercept time are obtained which are the forecasted coordinates of the intercept point. Experimental results demonstrate performance of the proposed algorithm