N M Harwood (Air and Weapons Systems, Defence Science and Technology Laboratory, UK), M Rutten (Intelligence, Surveillance and Reconnaissance Division, Defence Science and Technology Organisation, AUSTRALIA), R P Donnelly (Air and Weapons Systems Defence Science and Technology Laboratory, UK)
Keywords: SSA
Abstract:
The UKs Defence Science and Technology Laboratory (DSTL) and Australia’s Defence Science and Technology Organisation (DSTO) are undertaking a collaborative effort in the analysis of orbital errors for the purposes of surveillance of space (SoSp), with emphasis on orbital estimation, sensor fusion and tasking sensor assets. Access to assets in both the UK and Australia will provide an opportunity to study the use of a small number of geographically diverse sensors for orbital catalogue creation and maintenance. This paper presents a method of analysing the orbital error distribution using a Monte-Carlo technique, which has been designed to include the effects of residual sensor bias errors. This technique is used to investigate the effect of sensor measurement uncertainties on the orbital position throughout the satellite orbit. The analysis includes the calculation of the posterior Cram?r-Rao lower bound, which gives a lower bound on the mean estimation error independent of the type of estimator. It is shown that the bound can be used as a performance prediction tool to compare the estimation accuracies of several configurations of sensors and networks. More general implications for the tasking of SoSp sensors will be discussed.
Date of Conference: September 11-14, 2012
Track: Poster