# Integrated Space Domain Awareness and Communication System

arXiv: https://arxiv.org/abs/2211.10260 · HTML: https://mlsanity.com/paper/2211.10260/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 27 references that are in the map.
- First posted on arXiv 18 Nov 2022.

## Builds on (most cited first, 4 of 4)

- [Adam: A Method for Stochastic Optimization](https://mlsanity.com/paper/1412.6980/) (2014)
- [Massive MIMO Transmission for LEO Satellite Communications](https://mlsanity.com/paper/2002.08148/) (2020)
- [LEO Satellites in 5G and Beyond Networks: A Review from a Standardization Perspective](https://mlsanity.com/paper/2110.08654/) (2021)
- [Intermittent Jamming against Telemetry and Telecommand of Satellite Systems and A Learning-driven Detection Strategy](https://mlsanity.com/paper/2107.06181/) (2021)

## Built on by (most cited first, 2 of 2)

- [Secure and Robust Communications for Cislunar Space Networks](https://mlsanity.com/paper/2310.09835/) (2023)
- [Cyber Physical Awareness via Intent-Driven Threat Assessment: Enhanced Space Networks with Intershell Links](https://mlsanity.com/paper/2508.16314/) (2025)

## Abstract (arXiv)

Space has been reforming and this evolution brings new threats that, together with technological developments and malicious intent, can pose a major challenge. Space domain awareness (SDA), a new conceptual idea, has come to the forefront. It aims sensing, detection, identification and countermeasures by providing autonomy, intelligence and flexibility against potential threats in space. In this study, we first present an insightful and clear view of the new space. Secondly, we propose an integrated SDA and communication (ISDAC) system for attacker detection. We assume that the attacker has beam-steering antennas and is capable to vary attack scenarios, such as random attacks on some receiver antennas. To track random patterns and meet SDA requirements, a lightweight convolutional neural network architecture is developed. The proposed ISDAC system shows superior and robust performance under 12 different attacker configurations with a detection accuracy of over 97.8%.