Accession Number : ADA259039


Title :   Aircraft Trajectory Tracking and Prediction


Descriptive Note : Final rept. Sep 1991-Sep 1992


Corporate Author : DETROIT MERCY UNIV MI DEPT OF MECHANICAL ENGINEERING


Personal Author(s) : Cattani, Luis C ; Eagle, Paul J ; Lin, Zhud ; Liu, Xin


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/a259039.pdf


Report Date : Oct 1992


Pagination or Media Count : 51


Abstract : Regression modelling of trajectory measurement data was examined as a means for improving the performance of aircraft trajectory tracking and prediction. Regression models were used for adaptively removing measurement noise from trajectory observations and extrapolating trajectory measurements. A comparative study was done between three models of aircraft dynamics used in an extended Kalman filter: a strictly translational model, an attitude/translation model, and an attitude/translation model that uses vehicle specific inertial characteristics. Adaptive regression models were used for measurement accuracy enhancement. Comparisons were also made between errors resulting from position and attitude predictions using Runge-Kutta integration and extrapolated regression models.


Descriptors :   *TRACKING , *TRAJECTORIES , MEASUREMENT , AIRCRAFT , PREDICTIONS , DYNAMICS , INTEGRATION , TRANSLATIONS , NOISE , VEHICLES , ERRORS , ACCURACY , COMPARISON , OBSERVATION , AUGMENTATION


Subject Categories : Guided Missile Traj, Accuracy and Ballistics


Distribution Statement : APPROVED FOR PUBLIC RELEASE