The space environment has become highly congested due to the increasing space debris,
seriously threatening the safety of orbiting spacecraft. Space-based situational awareness …

A machine learning (ML) approach has been proposed to improve orbit prediction accuracy
in previous studies. In this paper, the artificial neural network (ANN) model is investigated for …

As the whole space segment of satellites in low Earth orbits (LEO) grows, simulations of
positioning, navigation, and timing (PNT) through LEO satellites are needed to understand …

The predictability of droughts in China was investigated using a series of statistical, dynamic
and hybrid models. The results indicate that, statistical models exhibit better skill in …

Accurate orbit prediction (OP) of space debris is vital in space situation awareness (SSA)
related tasks, such as space collision warnings. However, owing to the sparse and low …

Angles-only relative orbit determination for space situational awareness is subjected to a
well-known range observability problem, that is, the range between two spacecraft is weakly …

Orbit determination (OD) for spacecraft with unknown maneuver is always a challenging
task. This paper proposes a novel framework for efficiently solving continuously …

In this paper, the recently developed machine learning (ML) approach to improve orbit
prediction accuracy is systematically investigated using three ML algorithms, including …

Efficient and high precision orbit prediction is increasingly crucial for improved Space
Situational Awareness. Due to the lack of the required information such as space …

The capability accurately and timely detect a resident space object (RSO) maneuver is a
critical task for monitoring space activities. This paper presents a data-driven Gaussian …