Target Acceleration Estimation from Radar Position Data using Neural Network
Keywords: Kalman filter, artificial neural network, line-of-sight, feedforward neural network, target acceleration estimation, augmented proportional navigation
AbstractThis 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.
How to Cite
Sarkar, A., Vathsal, S., Sundaram, S., & Mukhopadhay, S. (2005). Target Acceleration Estimation from Radar Position Data using Neural Network. Defence Science Journal, 55(3), 313-328. https://doi.org/10.14429/dsj.55.1995
Special Issue Papers
Copyright (c) 2016 Defence Science Journal
where otherwise noted, the Articles on this site are licensed under Creative Commons License: CC Attribution-Noncommercial-No Derivative Works 2.5 India