scholarly journals Simulation of RSO Images for Space Situation Awareness (SSA) Using Parallel Processing

Sensors ◽  
2021 ◽  
Vol 21 (23) ◽  
pp. 7868
Author(s):  
Ryan Clark ◽  
Yanchun Fu ◽  
Siddharth Dave ◽  
Regina Lee
Keyword(s):  
Parallel Processing ◽  
Situation Awareness ◽  
Commercial Grade ◽  
Computational Speed ◽  
Space Objects ◽  
Realistic Representation ◽  
Order Of Magnitude ◽  
Resident Space Objects ◽  
Identification And Characterization ◽  
Auroral Imager

With the rapid increase in resident space objects (RSO), there is a growing demand for their identification and characterization to advance space simulation awareness (SSA) programs. Various AI-based technologies are proposed and demonstrated around the world to effectively and efficiently identify RSOs from ground and space-based observations; however, there remains a challenge in AI training due to the lack of labeled datasets for accurate RSO detection. In this paper, we present an overview of the starfield simulator to generate a realistic representation of images from space-borne imagers. In particular, we focus on low-resolution images such as those taken with a commercial-grade star tracker that contains various RSO in starfield images. The accuracy and computational efficiency of the simulator are compared to the commercial simulator, namely STK-EOIR to demonstrate the performance of the simulator. In comparing over 1000 images from the Fast Auroral Imager (FAI) onboard CASSIOPE satellite, the current simulator generates both stars and RSOs with approximately the same accuracy (compared to the real images) as STK-EOIR and, an order of magnitude faster in computational speed by leveraging parallel processing methodologies.

scholarly journals The Ad Hoc Back-End of the BIRALET Radar to Measure Slant-Range and Doppler Shift of Resident Space Objects

Electronics ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 577
Author(s):  
Luca Schirru ◽  
Tonino Pisanu ◽  
Angelo Podda
Keyword(s):  
Doppler Shift ◽  
Space Debris ◽  
Ad Hoc ◽  
Low Earth Orbit ◽  
Slant Range ◽  
Radar Systems ◽  
The Earth ◽  
Space Objects ◽  
Resident Space Objects ◽  
Potential Issue

Space debris is a term for all human-made objects orbiting the Earth or reentering the atmosphere. The population of space debris is continuously growing and it represents a potential issue for active satellites and spacecraft. New collisions and fragmentation could exponentially increase the amount of debris and so the level of risk represented by these objects. The principal technique used for the debris monitoring, in the Low Earth Orbit (LEO) between 200 km and 2000 km of altitude, is based on radar systems. The BIRALET system represents one of the main Italian radars involved in resident space objects observations. It is a bi-static radar, which operates in the P-band at 410–415 MHz, that uses the Sardinia Radio Telescope as receiver. In this paper, a detailed description of the new ad hoc back-end developed for the BIRALET radar, with the aim to perform slant-range and Doppler shift measurements, is presented. The new system was successfully tested in several validation measurement campaigns, the results of which are reported and discussed.

scholarly journals Experimental Comparison of Radon Domain Approaches for Resident Space Object’s Parameter Estimation

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1298
Author(s):  
Selenia Ghio ◽  
Marco Martorella ◽  
Daniele Staglianò ◽  
Dario Petri ◽  
Stefano Lischi ◽  
...  
Keyword(s):  
Experimental Data ◽  
Rotation Period ◽  
Research Topic ◽  
Experimental Comparison ◽  
Rotational Period ◽  
Space Objects ◽  
Resident Space Objects ◽  
The Moment ◽  
Inverse Radon Transform ◽  
Inverse Radon

The fast and uncontrolled rise of the space objects population is threatening the safety of space assets. At the moment, space awareness solutions are among the most calling research topic. In fact, it is vital to persistently observe and characterize resident space objects. Instrumental highlights for their characterization are doubtlessly their size and rotational period. The Inverse Radon Transform (IRT) has been demonstrated to be an effective method for this task. The analysis presented in this paper has the aim to compare various approaches relying on IRT for the estimation of the object’s rotation period. Specifically, the comparison is made on the basis of simulated and experimental data.

scholarly journals Accelerated methods for direct computation of fusion alpha particle losses within, stellarator optimization

2020 ◽  
Vol 86 (2) ◽  
Author(s):  
Christopher G. Albert ◽  
Sergei V. Kasilov ◽  
Winfried Kernbichler
Keyword(s):  
Alpha Particle ◽  
Symplectic Integrators ◽  
Particle Loss ◽  
Early Classification ◽  
Statistical Computation ◽  
Computational Speed ◽  
Order Of Magnitude ◽  
Speed Up ◽  
Orbit Types ◽  
Optimization Loop

Accelerated statistical computation of collisionless fusion alpha particle losses in stellarator configurations is presented based on direct guiding-centre orbit tracing. The approach relies on the combination of recently developed symplectic integrators in canonicalized magnetic flux coordinates and early classification into regular and chaotic orbit types. Only chaotic orbits have to be traced up to the end, as their behaviour is unpredictable. An implementation of this technique is provided in the code SIMPLE (symplectic integration methods for particle loss estimation, Albert et al., 2020b, doi:10.5281/zenodo.3666820). Reliable results were obtained for an ensemble of 1000 orbits in a quasi-isodynamic, a quasi-helical and a quasi-axisymmetric configuration. Overall, a computational speed up of approximately one order of magnitude is achieved compared to direct integration via adaptive Runge–Kutta methods. This reduces run times to the range of typical magnetic equilibrium computations and makes direct alpha particle loss computation adequate for use within a stellarator optimization loop.

scholarly journals Analytic Free-Molecular Aerodynamics for Rapid Propagation of Resident Space Objects

2018 ◽  
Vol 55 (1) ◽  
pp. 27-36 ◽  
Author(s):  
Kenneth A. Hart ◽  
Kyle R. Simonis ◽  
Bradley A. Steinfeldt ◽  
Robert D. Braun
Keyword(s):  
Rapid Propagation ◽  
Space Objects ◽  
Resident Space Objects

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.

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