Target Acceleration Estimation from Radar Position Data using Neural Network

Sarkar, AK and Vathsal, S and Sundaram, Suresh and Mukhopadhay, S (2005) Target Acceleration Estimation from Radar Position Data using Neural Network. In: Defence Science Journal, 55 (3). pp. 313-328.

PDF doc.pdf - Published Version Restricted to Registered users only Download (986Kb) | Request a copy

Abstract

This work is a preliminary investigation on target manoeuvre estimation in real-time from the available measurements of noisy position data from tracking radar using an artificial neural network (ANN). Recently, simulation study of target manoeuvre estimation in real-time from the same position alone measurement using extended Kalman filter has been carried out in a simulated environment using measurements at 100 ms interval. The results reveal that the estimated acceleration consists of substantial error and lag, which is a stumbling block for guidance accuracy in real-time. So, the target acceleration has been estimated using the ANN with less error and lag than the same using Kalman estimator.

Item Type:	Journal Article
Additional Information:	Copyright of this article belongs to Defence Scientific Information Documentation Centre.
Keywords:	Kalman filter;artificial neural network;line-of-sight;feedforward neural network;target acceleration estimation;augmented proportional navigation
Department/Centre:	Division of Mechanical Sciences > Aerospace Engineering (Formerly, Aeronautical Engineering)
Date Deposited:	10 Feb 2010 11:45
Last Modified:	19 Sep 2010 04:56
URI:	http://eprints.iisc.ernet.in/id/eprint/17401

Actions (login required)

View Item