scholarly journals Uncertainty Quantification for Space Situational Awareness and Traffic Management

Sensors ◽  
2019 ◽  
Vol 19 (20) ◽  
pp. 4361 ◽  
Author(s):  
Samuel Hilton ◽  
Federico Cairola ◽  
Alessandro Gardi ◽  
Roberto Sabatini ◽  
Nichakorn Pongsakornsathien ◽  
...  
Keyword(s):  
Traffic Management ◽  
Situational Awareness ◽  
Mathematical Framework ◽  
Space Situational Awareness ◽  
Tracking Errors ◽  
Position Uncertainty ◽  
Management Framework ◽  
Space Objects ◽  
Resident Space Objects ◽  
Machine Systems

This paper presents a sensor-orientated approach to on-orbit position uncertainty generation and quantification for both ground-based and space-based surveillance applications. A mathematical framework based on the least squares formulation is developed to exploit real-time navigation measurements and tracking observables to provide a sound methodology that supports separation assurance and collision avoidance among Resident Space Objects (RSO). In line with the envisioned Space Situational Awareness (SSA) evolutions, the method aims to represent the navigation and tracking errors in the form of an uncertainty volume that accurately depicts the size, shape, and orientation. Simulation case studies are then conducted to verify under which sensors performance the method meets Gaussian assumptions, with a greater view to the implications that uncertainty has on the cyber-physical architecture evolutions and Cognitive Human-Machine Systems required for Space Situational Awareness and the development of a comprehensive Space Traffic Management framework.

scholarly journals Integrated Space Situational Awareness Systems: SDA and SSA – Advantages and Limitations

2021 ◽  
Vol 50 ◽  
pp. 1-15
Author(s):  
Małgorzata Polkowska ◽  
Keyword(s):  
Situational Awareness ◽  
Space Situational Awareness ◽  
Space Systems ◽  
Space Domain ◽  
The Sustainable Development ◽  
Us Military ◽  
Comprehensive Knowledge ◽  
The Us ◽  
Space Objects ◽  
Space Infrastructure

SDA (Space Domain Awareness) and SSA (Space Situational Awareness – SSA) have been defined as comprehensive knowledge of space objects and the ability to track, understand, and predict their future location. The purpose of the article is to present SSA initiatives to protect space systems, which are now recognized as fundamental assets of the sustainable development of each country. The destruction of even a part of the space infrastructure can have severe consequences for the security of citizens and economic activity. These systems assume the combination of all data obtained by various entities operating in space and Earth to create a common database. The SSA system was created based on the US military programme SDA (Space Domain Awareness); SSA and SDA are almost similar, but SDA is a new term replacing SSA, which existed previously. SDA is a better and improved SSA. Increasingly, the SSA programme is part of national and EU space strategies, but it is not yet possible to include it in international space law.

Multi-objective optimization using parallel simulation for space situational awareness

2018 ◽  
Vol 16 (2) ◽  
pp. 145-157
Author(s):  
Michael S Felten ◽  
John M Colombi ◽  
Richard G Cobb ◽  
David W Meyer
Keyword(s):  
High Performance ◽  
Situational Awareness ◽  
National Policy ◽  
Low Earth Orbit ◽  
Total System ◽  
Space Situational Awareness ◽  
Multi Objective ◽  
Multi Objective Genetic Algorithm ◽  
Space Objects ◽  
Synchronous Orbit

Improving space situational awareness (SSA) remains one of the Department of Defense’s (DoD) top priorities. Current research has shown that the modeling of geosynchronous orbit (GEO) SSA architectures can help identify optimal combinations of ground- and space-based sensors. This paper extends previous research by expanding design boundaries and refining the methodology. A multi-objective genetic algorithm was used to examine this increased trade-space containing 1022 possible design combinations. The results of the optimizer clearly favor 1.0 m aperture ground telescopes combined with 0.15 m aperture sensors in a 12-satellite geosynchronous polar orbit (GPO) constellation. The GPO regime offers increased access to GEO resident space objects (RSO) since other orbits are restricted by a 40° solar exclusion angle. When performance is held constant, a GPO satellite constellation offers a 22.4% reduction in total system cost when compared to Sun synchronous orbit (SSO), equatorial low earth orbit (LEO), and near-GEO constellations. Parallel high-performance computing provides the possibility of solving an entirely new class of complex problems of interest to the DoD. The results of this research can educate national policy makers on the benefits of proposed upgrades to current and future SSA systems.

scholarly journals Task Planning for Multiple-Satellite Space-Situational-Awareness Systems

Aerospace ◽  
2021 ◽  
Vol 8 (3) ◽  
pp. 73
Author(s):  
Yutao Chen ◽  
Guoqing Tian ◽  
Junyou Guo ◽  
Jie Huang
Keyword(s):  
Situational Awareness ◽  
Space Situational Awareness ◽  
Task Planning ◽  
Single Object ◽  
Discrete Particle Swarm Optimization ◽  
Space Object ◽  
Contract Net ◽  
Planning Framework ◽  
Multiple Tasks ◽  
Space Objects

Space situational awareness (SSA) plays an important role in maintaining space advantages. Task planning is one of the key technologies in SSA to allocate multiple tasks to multiple satellites, so that a satellite may be allocated to supervise multiple space objects, and a space object may be supervised by multiple satellites. This paper proposes a hierarchical and distributed task-planning framework for SSA systems with focus on fast and effective task planning customized for SSA. In the framework, a global task-planner layer performs satellite and object clustering, so that satellites are clustered into multiple unique clusters on the basis of their positions, while objects are clustered into multiple possibly intersecting clusters, hence allowing for a single object to be supervised by multiple satellites. In each satellite cluster, a local task planner performs distributed task planning using the contract-net protocol (CNP) on the basis of the position and velocity of satellites and objects. In addition, a customized discrete particle swarm optimization (DPSO) algorithm was developed to search for the optimal task-planning result in the CNP. Simulation results showed that the proposed framework can effectively achieve task planning among multiple satellites and space objects. The efficiency and scalability of the proposed framework are demonstrated through static and dynamic orbital simulations.

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