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Boone, Jack N.

Publications and source records attributed to Boone, Jack N..

Generalized covariance analysis for partially autonomous deep space missions

A new covariance analysis method is presented that is suitable for the evaluation of multiple impulsive controllers acting on some stochastic process x. The method accommodates batch and sequential estimators with equal ease and accounts for time-delay effects in a natural manner. The formalism is developed in terms of a generalized state vector that is formed from the system state vector x, augmented by various fixed epoch estimates, and a data vector formed from discrete time observations of the system. Recursions are developed for time transition, measurement incorporation, and impulsive control updating of the generalized covariance matrix. Means of limiting the dimensional growth of the generalized state vector via the processes of estimator epoch adjustment and measurement vector deflation are described and the application of numerically stable matrix factorization methods to the generalized covariance recursions is outlined. The method is applied to the Magellan spacecraft to demonstrate the capability of ground-based optimal estimation and control of gyro/star scanner misalignment.

Boone, Jack N.↗

Magellan in-flight gyro/star scanner misalignment calibration

Techniques are described for the in-flight calibration of gyro/star scanner misalignments for the Magellan spacecraft. The poor observability of one of the six components of misalignment is discussed in the context of a simple least-squares estimation model. The assumptions that lead to singularity in the information matrix are explicitly stated and it is shown that the singularity persists for all scanner slit configurations using only two slits, regardless of slit geometry or separation. A set of misalignment error state variables, a configuration of three stars, and a maneuver/scan sequence is described which yields a well-conditioned information matrix for least-squares estimation of five of the six misalignments. Finally, it is shown by convariance simulation that ground-based optimal estimation can satisfactorily resolve all six components of the misalignment error when more than two star scanner slits are used.

Boone, Jack N.↗

Generalized Covariance Analysis For Remote Estimators

Technique developed to predict true covariance of stochastic process at remote location when control applied to process both by autonomous (local-estimator) control subsystem and remote (non-local-estimator) control subsystem. Intended orginally for design and evaluation of ground-based schemes for estimation of gyro parameters of Magellan spacecraft. Applications include variety of remote-control systems with and without delays. Potential terrestrial applications include navigation and control of industrial processes.

Boone, Jack N.↗