Target Acceleration Estimation from Radar Position Data using Neural Network

Defence Science Journal

A.K. Sarkar³  Suresh Sundaram²  S. Vathsal⁴  S. Mukhopadhay¹ 

[1] Indian Insttute of Technology, Kharagpur;Indian Institute of Science, Bangalore;Defence Research & Development Laboratory, Hyderbad;Directorate of ER & IPR, New Delhi

关键词: Kalman filter;    artificial neural network;    line-of-sight;    feedforward neural network;    target acceleration estimation;    augmented proportional navigation;   

DOI  :  

学科分类：社会科学、人文和艺术（综合）

来源: Defence Scientific Information & Documentation Centre

【 摘 要 】

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.

【 授权许可】

Unknown