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.
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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|
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