Recent advancements in deep learning applications and methods for autonomous navigation: A comprehensive review

AA Golroudbari, MH Sabour - arXiv preprint arXiv:2302.11089, 2023 - arxiv.org
This review article is an attempt to survey all recent AI based techniques used to deal with
major functions in This review paper presents a comprehensive overview of end-to-end …

[HTML][HTML] Deep learning methods for space situational awareness in mega-constellations satellite-based internet of things networks

F Massimi, P Ferrara, F Benedetto - Sensors, 2022 - mdpi.com
Artificial Intelligence of things (AIoT) is the combination of Artificial Intelligence (AI)
technologies and the Internet of Things (IoT) infrastructure. AI deals with the devices' …

[HTML][HTML] Deep learning-based motion style transfer tools, techniques and future challenges

SMA Akber, SN Kazmi, SM Mohsin, A Szczęsna - Sensors, 2023 - mdpi.com
In the fourth industrial revolution, the scale of execution for interactive applications increased
substantially. These interactive and animated applications are human-centric, and the …

Review of sensor tasking methods in Space Situational Awareness

C Xue, H Cai, S Gehly, M Jah, J Zhang - Progress in Aerospace Sciences, 2024 - Elsevier
To ensure the secure operation of space assets, it is crucial to employ ground and/or space-
based surveillance sensors to observe a diverse array of anthropogenic space objects …

Optimal Sensor Tasking for Space Domain Awareness via a Beam A*-Search Algorithm

L Federici, A D'Ambrosio, R Furfaro… - The Journal of the …, 2024 - Springer
Sensor tasking for space domain awareness is a complex problem that involves scheduling
observations of objects in space from one or multiple sensors, usually telescopes. This …

Deep learning‐based space debris detection for space situational awareness: A feasibility study applied to the radar processing

F Massimi, P Ferrara, R Petrucci… - IET Radar, Sonar & …, 2024 - Wiley Online Library
The increasing number of space objects (SO), debris, and constellation of satellites in Low
Earth Orbit poses a significant threat to the sustainability and safety of space operations …

Multi-Spacecraft Predictive Sensor Tasking for Cislunar Space Situational Awareness

K Tomita, Y Shimane, K Ho - arXiv preprint arXiv:2310.04894, 2023 - arxiv.org
This paper delves into the predictive sensor tasking algorithm for the multi-observer, multi-
target sensor setting, leveraging the Extended Information Filter (EIF). Conventional …

DebriSense: Terahertz-based Integrated Sensing and Communications (ISAC) for Debris Detection and Classification in the Internet of Space (IoS)

H Dong, OB Akan - arXiv preprint arXiv:2408.13552, 2024 - arxiv.org
The proliferation of Low Earth Orbit (LEO) satellite constellations has intensified the
challenge of space debris management. This paper introduces DebriSense-THz, a novel …

An Integer Programming Approach to Observation Scheduling for Space Domain Awareness

G Nations, J Fletcher - 2024 IEEE Aerospace Conference, 2024 - ieeexplore.ieee.org
Satellites underpin all economic, military, and scientific activity in space. Ground-based
telescope observations provide much of the tracking information that enables collision …

[PDF][PDF] Scalable Multi-Agent Sensor Tasking Using Deep Reinforcement Learning

PM Siew, T Smith, R Ponmalai… - Proceedings of the …, 2023 - amostech.com
Satellite launches have seen a dramatic increase in recent years, driven by the growth of
commercial and government constellations for a range of applications, including …