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Postflight data analysis by means of adaptive, iterated, extended Kalman filtering

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1 Author(s)
J. Mendel ; University of Southern California, Los Angeles, CA, USA

This paper describes a specific postflight data analysis (PFDA) technique, which is termed adaptive, iterated, extended Kalman filtering (AIEKF), and illustrates the application of the PFDA tool to the estimation of aerodynamic coefficients ( C_{x}, C_{N}, and C_{m} ) for a single-axis model of a thrust-vector-controlled missile. It is demonstrated that PFDA embraces many areas of interest to control specialists, such as simulation of nonlinear systems, estimation, optimization, and validation.

Published in:

IEEE Transactions on Automatic Control  (Volume:19 ,  Issue: 5 )