Thomas Kelecy, L3 Harris; Emily Lambert, L3 Harris; Benjamin Sunderland, L3 Harris; Vivek Desai, University of Texas, Austin
Keywords: USKF, Calibration, Optical, Range
Abstract:
Building on the research performed on calibration of optical sensors, which investigated the dynamic calibration of electro-optical data used to support space situational awareness, the research being presented examines approaches for the dynamic calibration of radar sensor data, techniques for cross correlation of optical and radar measurements, and methods for determining sensor quality information, long term trends and biases.
The introduction of new sensors, or the use of third-party sensors, within the space situational awareness architecture is difficult and lengthy, often taking a number of years to introduce to the system. Techniques that would enable more rapid assessment of third-party sensors, determination of sensor quality and integrity would enable external sensors to be utilized more readily and significantly improve the space operational awareness.
The proposed research activity would draw on radar data from commercial network providers and other publicly available range observation sources. The results of the research would be equally applicable however to sensors operating on the classified domain. The dynamic Unscented Schmidt Kalman Filter (USKF) algorithms, already established for optical sensor calibration, is tested and validated for multiple data and multi-sensor calibration with emphasis on range data calibration.
Date of Conference: September 17-20, 2019
Track: Astrodynamics