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Thesis advisor, So Young Sohn

Thesis advisor, So Young Sohn

Since its establishment the Naval Space Surveillance Command (NAVSPASUR)in Dalhgren Virginia has been providing surveillance data (NAVSPASUR data sets) for thousands of space objects in a near earth orbit. To date, very little statistical analysis of these data sets in the form of a system performance evaluation has been conducted. The objective of this thesis is to provide NA VSPASUR with a statistical method to evaluate the system performance in terms of its capability of detecting space objects.. In this thesis six individual station models , as well as a system-wide model are estimated. Optimal probability levels for classifying predictions are additionally provided. The results being provided are obtained through the implementation of Logistic Regression analysis. The system- wide model estimated in this thesis, is superior in its prediction accuracy when compared to the previous mode! provided to NAVSPASUR in a September 1991, Naval Postgraduate School Master's Thesis. Finally an implementation program written in FORTRAN is given. This program provides a user friendly interface capability for predicting system performance in terms of its detection ability.

Since its establishment the Naval Space Surveillance Command (NAVSPASUR) in Dalhgren Virginia has been providing surveillance data (NAVSPASUR data sets) for thousands of space objects in a near earth orbit. To date, very little statistical analysis of these data sets in the form of a system performance evaluation has been conducted. The objective of this thesis is to provide NAVSPASUR with a statistical method to evaluate the system performance in terms of its capability of detecting space objects. In this thesis six individual station models, as well as a system-wide model are estimated. Optimal probability levels for classifying predictions are additionally provided. The results being provided are obtained through the implementation of Logistic Regression analysis. The system-wide model estimated in this thesis, is superior in its prediction accuracy when compared to the previous model provided to NAVSPASUR in a September 1991, Naval Postgraduate School Master's Thesis. Finally an implementation program written in FORTRAN is given. This program provides a user friendly interface capability for predicting system performance in terms of its detection ability.