Leviosa

Beirut | Mapping Space Trash in Real Time

Cracking the DNA Space Debris in Frequency Domain

High-Level Project Summary

We are proposing the application of Fourier Transform to obtain unique identification codes for debris populations in the frequency domain. The challenge was presented using WorldWind Java. A typical raw data signal was obtained using an Arduino experiment, and Matlab was used to apply the Fourier Transform. Variety of signals representing both different populations and distorted populations of the same type were used. It was found frequencies representing the same population are somehow maintained even if distorted. This method showed potential to identify debris populations without the need to measure every single debris in the population essential for early warning and collision measures

Link to Project "Demo"

https://drive.google.com/file/d/1eEPSuAu6ldZjSnN3nKlMS3KA94i62529/view?usp=sharing

Link to Final Project

https://drive.google.com/drive/folders/1i68olFZyALTsD5Epjs3uPhEaGM6Gi6qi?usp=sharing

Detailed Project Description

Using the NASA resources, we identified the problem by simulating the existing ground stations and population debris in Java. We noticed that there are possibly some blind spots. Hence, after some research we started to think about a feasible way to address this issue without the need to build new and expensive ground stations. In this challenge, we are proposing the application of existing mathematical method called the "Fourier transform" to obtain unique identification codes for trash and debris populations in the frequency domain.

Raw data from ground optical sensors were not available. Hence, to validate our method, we setup an Arduino experiment. The microcontroller was programmed in C. In the experimental setup, we used a modulated Light Emitting Diode to resemble the sun and passing debris. This flickering light resembles a passing debris in front of sun light and the light detector simulates the ground radar.

Then, we added noise, using MATLAB, to the obtained signals to make the signals more realistic. Variety of signals representing both different populations and distorted populations of the same type were used. After applying the Fourier Transform, it was found frequencies representing the same population are somehow maintained even if distorted. Different debris populations clearly showed different frequencies.

The frequencies signature not only distinguishes different populations by their size, shape and distance separation, but also distinguishes the same population even in distorted states. For example, even if some debris left the pack or rotated, we are still able to identify them as the same population. We believe this method could help existing tracking efforts. This allows to identify debris populations using small samples rather than measuring every single debris in time domain. Debris Population database is required as a prerequisite to make this successful in the future. We believe this method is useful for early warning measures and collision avoidance.

Space Agency Data

· The use of the NASA Data to obtain the locations of the US Space Surveillance Network was essential for simulating the challenge in WorldWind Java.

https://pds.nasa.gov/ds-view/pds/

This allowed us not only to evaluate the challenge in more detail but also to identify the potential blind spots with respect to the ground measuring instrumentation. Our debris mapping solution was proposed (tracking debris populations in the frequency domain instead of time domain) based on the NASA data above together with the open source Java available.

· We have also used the WorldWind Java, and the open source libraries “worldwind.jar” to be able to visualize the globe in a relatively shorter time.

https://worldwind.arc.nasa.gov/java/

This allowed us to visualize the ground stations and create a population debris. We were able to program the ground stations to have a certain field of view. This allowed us to identify the blind spots and propose a simple mathematical approach to analyze debris in the frequency domain.

· We have also used NASA Data to estimate the debris number, available orbits and speed. https://www.orbitaldebris.jsc.nasa.gov/modeling/engrmodeling.html

This also allowed us to create a realistic Arduino experiment to obtain some realistic raw data from a typical optical sensor or a telescope. The output data of this experiment, allowed us to apply the Fourier Transform and analyze our method as a potential towards mapping debris in the frequency domain. The experiment comprises of a flickering LED to resemble the sun and passing debris and a photodiode to represent the ground station or optical sensor.

Hackathon Journey

This is our first time entering a global challenge, it was an exhilarating experience and we thoroughly enjoyed our journey.

In this challenge, we learned how to conduct a review of literature, write our findings in a scientific manner, and use a variety of software. For example, we have used JAVA, MATLAB, and C programming, in order to validate our proposed solution. In addition, we have set an experiment using Arduino. We used a flickering Light Emitting Diode to represent sunlight and passing debris and a photodiode to represent the optical sensor ground station. We have had hands on experience setting up the experiment, which gave us a good knowledge of what it takes to have a successful running experiment from ordering components to taking measures and to reducing background noise. In MATLAB, we learned how to apply the Fourier transform (to convert the time domain signal to frequency domain) easily using the FFT command, and we added theoretical noise to the signal obtained from the Arduino experiment.

We found the topic interesting; it involved programming, and proposing new ideas. I liked this idea because it involves analyzing space and its existing debris, tracking methods and using NASA data. The outcome for our project we believe will make a change, by making our space safer by tracking debris and trash in real time. Thus, it would allow us to prevent further collisions and give us early warnings, and allow for safer space discoveries.

We overcame our setbacks and challenges by dedication and resilience. If we came across a challenge we would take a step back and look at the big picture, then we would go over the literature review and start looking into more details. If there were any issues that were relating to logistical issues, there were always alternatives that would not stop our progress.

Finally, we would like to thank Mr Antoine Tannous and his team from Lebanon, together with the volunteers from USEK University for their continued support throughout this competition. We would especially like to thank our parents for their mentoring and support and for giving us the opportunity to enter a big competition such as this.

References

Ground Stations Locations:

· https://pds.nasa.gov/ds-view/pds/

· https://en.wikipedia.org/wiki/United_States_Space_Surveillance_Network

Space Debris Information

· “Manual Procedure for Determining Position in Space from Onboard Optical Measurements”, a technical note by Harold A. Hamer, Langely Research Center, Langley Station, Hampton, Va.(1964)

· “Understanding Space Debris” causes, mitigations and issues (2015) www.aerospace.org/publications/crosslink-magazine

· “Literature Review: Space Debris, Track methods and the Danger of the Future Debris Environment” by Jorida Latifi, University of Minnesota, 2015

· “IAA Situation Report on Space Debris” by Christophe Bonnal, and Darren S. McKnight, 2016.

· www.terma.com (track report)

Worldwind java

· https://worldwind.arc.nasa.gov/web

· Pirotti et al. Open Geospatial Data, Software and Standards (2017) 2:4

DOI 10.1186/s40965-017-0016-5

· Orbit of satellites https://www.gano.name/shawn/JSatTrak/

· https://worldwind.earth/WorldWindJava/ (show examples

· https://www.npmjs.com/package/webworldwind-x for extending functionality of worldwind

· https://mikescodeprojects.com