Sensor scheduling with orbital uncertainty for space target tracking

Abstract

The orbit determination accuracy of space debris can be remarkably improved when it is observed by two space-based optical (SBO) sensors simultaneously. The key to observation with two SBO sensors is optimizing the pointings of sensors to maximize the length of the double coverage arc. The traditional sensor scheduling method is only based on the mean of the predicted target orbit, and its coverage performance degrades when the error of the predicted target orbit increases. In this paper, the double coverage probability (DCP) is employed as a sensor scheduling criterion with considered the uncertainty of the predicted target orbit. The DCP is obtained by calculating an integral of the probability density function of target position distribution. Furthermore, an approximate expression of the DCP is derived by simplifying the integral region to reduce the computational burden. The simulation results show that the proposed sensor scheduling method based on the DCP can provide a longer double coverage arc and higher orbit determination accuracy than the traditional method.