Estimation of singularities for intercept point forecasting

Author

Satish, A. ; Kashyap, Rangasami L.

Author_Institution

Sch. of Electr. Eng., Purdue Univ., West Lafayette, IN, USA

Volume

32

Issue

4

fYear

1996

fDate

10/1/1996 12:00:00 AM

Firstpage

1301

Lastpage

1310

Abstract

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

Keywords

Kalman filters; approximation theory; curve fitting; direction-of-arrival estimation; least squares approximations; missile guidance; motion estimation; polynomials; recursive estimation; target tracking; angle of interception; closed-form solution; cubic polynomial; direction of arrival; estimation of singularity; forecasted coordinates; intercept point; intercept point forecasting; intercept time; interceptor; maximum likelihood DOA estimation; nodal cubic curve; recursive approach; recursive least squares solution; target; Data acquisition; Direction of arrival estimation; Infrared sensors; Kalman filters; Maximum likelihood estimation; Radar tracking; Recursive estimation; Sensor arrays; Sensor fusion; Sensor systems; Target tracking; Trajectory;

fLanguage

English

Journal_Title

Aerospace and Electronic Systems, IEEE Transactions on

Publisher

ieee

ISSN

0018-9251

Type

jour

DOI

10.1109/7.543851

Filename

543851