Low-thrust maneuver anomaly detection of a cooperative asset using publicly available orbital data

Abstract

Abstract. This work presents a novel method to estimate perturbations with respect to nominal maneuver planning by exploiting Two-Line-Element (TLE) data as initial step, then moving on to Global Positioning System (GPS) processed data. The case study is a low-thrust engine validation mission in Low Earth Orbit. The first algorithm exploits a couple of TLEs as boundary conditions to set up a least-squares problem and find the tangential thrust magnitude and firing duration to best fit the bounding orbital states, making use of Taylor differential algebra and Picard iterations. The second one makes use of a sequence of GPS states to apply multistep finite differences and a root-finding algorithm to retrieve information about both thrust profile and firing bounding times.