In many Space Surveillance and Tracking (SST) operations, from the cataloguing of trackable space objects to orbit determination and correlation, ground-based measurements play a central role. In this frame, the monitoring and, if necessary, the update of the sensors' calibration parameters is of utmost importance to correctly evaluate the positions of tracked objects. In this work, a method for the metrological characterization of ground-based sensors for SST applications is implemented, and the performance of the developed sensor calibration tool is assessed. Starting from the acquisition of information about the sensor and data from Tracking Data Messages and Orbit Ephemeris Messages, and assuming a Gaussian distribution for all the observed parameters, the tool computes the residuals and outputs the main statistics for all the parameters of interest. The distributions of the residuals are analyzed to evaluate the statistical significance of the results and the robustness of the hypothesis of Gaussian distribution.

Metrological Characterization of Ground-based Sensors for Space Surveillance and Tracking

Matta, Walter
Supervision
2021-01-01

Abstract

In many Space Surveillance and Tracking (SST) operations, from the cataloguing of trackable space objects to orbit determination and correlation, ground-based measurements play a central role. In this frame, the monitoring and, if necessary, the update of the sensors' calibration parameters is of utmost importance to correctly evaluate the positions of tracked objects. In this work, a method for the metrological characterization of ground-based sensors for SST applications is implemented, and the performance of the developed sensor calibration tool is assessed. Starting from the acquisition of information about the sensor and data from Tracking Data Messages and Orbit Ephemeris Messages, and assuming a Gaussian distribution for all the observed parameters, the tool computes the residuals and outputs the main statistics for all the parameters of interest. The distributions of the residuals are analyzed to evaluate the statistical significance of the results and the robustness of the hypothesis of Gaussian distribution.
2021
978-1-7281-7556-0
Ground-based Sensors
Sensor Calibration
Space Surveillance and Tracking
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14085/25561
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