Maximum Likelihood Estimation For Distributed Parameter Models of Flexible Spacecraft

Abstract

Because of the large size and flexibility of certain spacecraft, it is not possible to determine with suitable accuracy their structural dynamic characteristics from ground tests. It is necessary, therefore, to analyze orbital response data to refine the a priori parameters of models of the structural dynamics. Because of the high order and complexity of the relationships, the number of unknown model parameters can become unmanageable if each is assumed to be independent of each other. For many spacecraft it is possible to use distributed parameter models, thereby reducing the number unknown parameters. An important side benefit is that the model accuracy is increased.Experimental data from the NASA Solar Array Flight Experiment (SAFE) is analyzed by applying a maximum likelihood estimation algorithm to the task of estimating the unknown parameters of a distributed parameter model of the SAFE configuration. Both the out-of-plane bending and torsion of the solar array are modeled using partial differential equations. A truncated form of the model is used in the estimation algorithm and the higher modes are deduced from the distributed parameter model. The use of maximum likelihood estimation and distributed parameter models results in the most accurate model possible. The Solar Array Flight Experiment offers a unigue opportunity to demonstrate the procedures for modelling complex, flexible spacecraft in the preparation for more complex configurations such as the NASA Manned Space Station.