Techniques are presented for improving methods of aircraft identification and trajectory prediction. This work represents an extension of the advanced trackers that use both translation and attitude data to improve accuracy of trajectory tracking and prediction. The novel extension in this work deals with the development of a new tracking algorithm based on a radius of curvature estimator, use of regression based artificial measurements during the prediction interval and development of aircraft identification techniques for vehicles being tracked based on remote trajectory measurements. The procedure was evaluated with actual position and attitude trajectory data for a F-14A, AV-8B and A-6 aircraft acquired during training flights.
Aircraft Identification, Trajectory Tracking and Prediction
1995
88 pages
Report
No indication
English
Aircraft , Radiofrequency Detection , Flight training , Iff systems , Training aircraft , Algorithms , Measurement , Predictions , Kalman filtering , Tracking , Accuracy , Estimates , Regression analysis , Identification , Curvature , Trajectories , Remote systems , Intervals , F-14a aircraft , Av-8b aircraft , A-6 aircraft
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