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SUMMER 2018 INTERNSHIPS
MIT HAYSTACK OBSERVATORY
Westford, Massachusetts

The 2018 REU application will be available later this month: please check back.

Current MIT 2018 summer internship projects:

  1. Development of a spectrometer to measure the hydroxyl radical (OH) in the mesosphere
  2. LEGO: Using dark clouds in the Milky Way to understand distant galaxies
  3. Autonomous spacecraft navigation with small radio antennas
  4. Avionics for an Antarctic ice penetrator, an air-droppable polar robotic instrument
  5. Deblurring an echo: Sparsity applied to the radar inverse problem
  6. Deep learning for satellite data processing
  7. Observing black holes with the Event Horizon Telescope
  8. Millstone Hill radar plasma-line analysis
  9. Open source drone platform for radio science using software-defined radios
  10. Radio location finding using an electromagnetic vector sensing for conservation ecology

  1. Development of a spectrometer to measure the hydroxyl radical (OH) in the mesosphere
  2. Mentors: Alan Rogers [aeer at haystack.mit.edu]
    Phil Erickson [pje at haystack.mit.edu]

    imageStudent qualifications: Students in EE with a background in hardware and software are encouraged to apply.

    Project description: Haystack Observatory has developed an ozone spectrometer using 45 cm diameter TV dishes with their satellite TV low noise block down converter feeds (LNBFs) which operate in the 11–13 GHz band for observations of 11072 MHz line of ozone in the mesosphere. These spectrometers provide worldwide scientific data on the chemistry and circulation in the region about 100 km in altitude. Currently these 6 spectrometers are operating in the northeast USA along with a spectrometers in the UK, Finland, and the Antarctic.

    Recently, an LNBF which covers the 13–14 GHz band has become available, which opens up the possibility of observing the spectral lines of OH in the J = 7/2 excited state at 13433.94, 13434.64, 13441.42, 13442.11 MHz. These are similar to the well known 1612, 1665, 1667, 1720 MHz rotational lines in the J = 3/2 ground state. The 13 GHz lines have not been observed before but should be observable in the mesosphere since millimeter and infrared lines of OH have been observed in the mesosphere. The rotational lines are split into hyperfine states. The lines with a change in spin will be shifted by the earth's magnetic field via the Zeeman effect while the center line is not shifted by the earth's field. Observations using spectrometers based on low cost satellite TV electronics could lead to a better understanding of the chemistry in the mesosphere and its dependence on upper atmosphere winds, solar UV radiation and solar proton events. This project involves tests of the spectrometer and further development of software for acquisition and analysis of the OH and ozone lines.




  3. LEGO: Using dark clouds in the Milky Way to understand distant galaxies
  4. Mentor: Jens Kauffmann [jkauffma at haystack.mit.edu]

    Student qualifications: Willingness to learn a programming language, ideally demonstrated by previous programming work.

    Project description:  It is hard to study fine details even in the most nearby galaxies. To give an example, some of the most exciting research today focuses on the formation of stars in the Milky Way and other galaxies. The star-forming sites in the Milky Way, also known as dark clouds, can be studied at an amazing level of detail. We can actually see how individual stars and planets form in our neighborhood. However, if we turn to galaxies, even the best telescopes available today cannot resolve dark clouds at a meaningful level of detail. Astronomers have therefore developed tricks to study the structure of clouds they cannot resolve. They study radiation from a variety of molecules, e.g. hoping that some molecules provide clues on dense gas while others might indicate that a dark cloud is being stirred up by embedded young stars. These are fascinating methods—but they have never been tested in the Milky Way. The LEGO survey therefore surveys dark clouds in the Milky Way to perform such tests. This teaches us lessons about star formation in the Milky Way and other galaxies. If you join this program, you will become part of an international collaboration that includes researchers from the US, the EU, Chile, and Japan.




  5. Autonomous spacecraft navigation with small radio antennasLEGO: Using dark clouds in the Milky Way to understand distant galaxies
  6. Mentors: Michael Hecht [mhecht at haystack.mit.edu]
    Vincent Fish [vfish at haystack.mit.edu]

    imageStudent qualifications: Facility with instrumentation, software, and data analysis.

    Project description: Since the dawn of interplanetary exploration, spacecraft exploring deep space have been navigated from Earth using tools such as Doppler ranging. While highly effective, the system is expensive and cumbersome, depending on a small number of very large Deep Space Network (DSN) antennas, and cannot be used when the spacecraft is behind the sun or otherwise out of Earth line-of-site. As CubeSats and other micro-satellites move beyond Earth orbit, the DSN will become increasingly overloaded.

    In principle, spacecraft could navigate themselves if they had proper references and sufficient intelligence. While sightings on the fixed stars only allow spacecraft to orient themselves, the sky is also full of time and frequency standards, in the form of astronomical masers and pulsars, that would allow spacecraft to determine their positions and velocities without assistance from Earth.

    For this REU project, the student will explore this concept using the Small Radio Telescope (SRT, as described on the Haystack website) as a proxy for a small antenna that might deploy from a CubeSat. The SRT hardware and software will be updated to get the best possible L-band spectroscopic resolution, the radio-frequency interference (RFI) spectrum will be characterized, and data will be acquired and analyzed to demonstrate the navigation potential of millisecond pulsars and the weak but stable OH masers.




  7. Avionics for an Antarctic ice penetrator, an air-droppable polar robotic instrument
  8. Mentors: Pedro Elosegui [pelosegui at haystack.mit.edu]
    Jason SooHoo [jsoohoo at haystack.mit.edu]

    imageStudent qualifications: Computer science, aero and electrical engineering, physics, or a related field with an interest in computer systems, avionics, and signal processing techniques. A basic knowledge of embedded computers, Linux, and real-time operating systems. Excellent programming skills in Python and the C programming languages.

    Project description: The student will take to final stage an existing laboratory prototype of an avionics (hardware/software) system to conduct polar studies. Avionics tasks include autonomous control of data acquisition, processing, storage, and transmission from scientific sensors to be deployed in remote extreme environments to monitor the current state of the cryosphere, particularly the Antarctic ice shelves. Monitoring sensors include a geodetic-quality GPS receiving system, a geophysics-grade broadband seismometer, an inertial navigation system, meteorological variables, and impact sensors. Science data transmission involves satellite communications via Iridium transceivers. We intend the final product of this project to be the avionics that will be tested in Greenland and deployed in Antarctica.




  9. Deblurring an echo: Sparsity applied to the radar inverse problem
  10. Mentor: Ryan Volz [rvolz at haystack.mit.edu]

    imageStudent qualifications: Strong programming skills and experience with (or desire to learn) Python.

    Project description: The basic function of a radar is to transmit a radio signal and receive reflections of that signal from targets of interest. The received signal is examined for echoes of the transmitted waveform in order to identify targets and measure their properties based on how the signal is transformed. Complicating these measurements is the ambiguity, or blurring, imposed by the transmitted waveform. Traditionally, the waveform is designed to minimize this effect in the context of a given application. The aim of this project is to explore new methods of processing the received data to reduce or remove the ambiguity and thereby improve the quality of the radar measurements.

    At Haystack, we are interested in scientific targets present in the upper atmosphere/ionosphere such as meteors, plasma irregularities, and the ionosphere itself. These types of targets, as well as those in many other radar applications, are sparse in the sense that they can be described simply with an appropriate model. This foreknowledge of sparsity enables the use of deblurring techniques that are an active area of research across many disciplines and applications. The specific focus of the project will depend on the student's skills and interests, and it could emphasize any of the following: nonlinear signal processing, optimization algorithms, programming, and data analysis.




  11. Deep learning for satellite data processing
  12. Mentors: Victor Pankratius [pankrat at haystack.mit.edu]
    Guillaume Rongier [grongier at haystack.mit.edu]
    Cody Rude [cmrude at haystack.mit.edu]

    imageStudent qualifications: Computer science/geoscience/remote sensing students with an interest in Artificial Intelligence. Python programming experience required.

    Project description: Deep neural networks have recently produced impressive results for classification problems in Big Data image processing, and are currently a hot topic in Artificial Intelligence research. This project will provide an opportunity to learn more about this area and explore the development new deep learning neural networks for remote sensing data processing in Python. In particular, we will focus on Interferometric Synthetic-Aperture Radar (InSAR) satellites that allow the creation of interferograms to discover geophysical phenomena and natural hazards, such as earth surface deformations associated with earthquakes, volcano eruptions, landslides, or groundwater depletion. This work also aims to improve the separation of various noise sources and enhance the scalability of detections on large data sets.




  13. Observing black holes with the Event Horizon Telescope
  14. Mentors: Vincent Fish [vfish at mit.edu]
    Kazunori Akiyama [kazu at haystack.mit.edu]

    imageStudent qualifications: This project is well suited to a student with a background in basic physics and astronomy. Experience in computer programming or a high-level scientific analysis package is desirable.

    Project description: The Event Horizon Telescope (EHT) is an array of millimeter-wavelength facilities that observe the nearest supermassive black holes using the technique of very long baseline interferometry. The EHT is uniquely capable of resolving structures on angular scales of a few Schwarzschild radii around the black holes in the Galactic Center (Sgr A*) and the nearby giant elliptical galaxy Virgo A (M87). The goals of the EHT include testing general relativity and furthering our understanding of the astrophysics of accretion and outflow processes around black holes.

    EHT observations of Sgr A* in recent years have been used to establish that Sgr A* has an event horizon, to identify the inclination of the accretion disk, to place limits on the spin of the black hole, and to verify that the mechanism of variability occurs at the inner edge of the accretion flow. We are in the process of analyzing and interpreting data from the latest EHT observations, and additional observations are expected in spring 2015. We are seeking a student to assist in the analysis and calibration of EHT data.




  15. Millstone Hill radar plasma-line analysis
  16. Mentors: Shunrong Zhang [shunrong at mit.edu]
    Phil Erickson [pje at haystack.mit.edu]
    Bill Rideout [brideout at haystack.mit.edu]

    image

    Student qualifications: We seek a detail-oriented and motivated student who has some experience with MATLAB or Python analysis and who can explore a fairly large volume of data for statistical and case studies. A science background is preferred, and an interest in space, astronomical, atmospheric, or geophysical science is helpful.

    Project description: Electron density is a fundamental parameter for characterization of the ionosphere and the upper atmosphere. It is sensitive to a variety of processes that come from above (the sun and the magnetosphere) and below (from the lower atmosphere down to the earth’s surface). Measurements of electron density are key to many space science investigations. Haystack Observatory provides electron density measurements as a NSF Geospace Facility with our large and powerful ionospheric radar at Millstone Hill using the incoherent scatter radar (ISR) technique. In the past few years, the radar method we use allows us to make new and very accurate electron density measurements using a technique called plasma-line analysis. This technique was formerly very difficult, but modern radio tools have greatly eased its implementation and scientific use. Additionally, we have continued to separately make local electron density measurements near Millstone Hill using a separate and traditional ionosonde technique, a practice that has continued since our first ISR measurements in the 1960s.

    This project will explore use of the existing high accuracy plasma-line data obtained from the Millstone Hill ISR systems since 2016. The two main tasks are (1) a comparative scientific and technical comparison study using both plasma-line data and the ionospheric ionosonde data, and (2) studies of solar and/or geospace storm induced upper atmospheric waves and their propagation as revealed from the plasma-line data in conjunction with other observational techniques.



  17. Open source drone platform for radio science using software-defined radios
  18. Mentors: John Swoboda [swoboj at mit.edu]
    Ryan Volz [rvolz at haystack.mit.edu]

    image Student qualifications: Python programming, signal processing background.

    Project description: Develop a prototype drone platform that can use software radios to perform radio applications. The student will use open source platforms such as the Pixhawk flight controller and Digital RF to develop a test bed system that can be used for various tasks including sensor calibration and validation.




  19. Radio location finding using an electromagnetic vector sensing for conservation ecology
  20. Mentors: Frank Lind [flind at haystack.mit.edu]
    Bryan Windmiller [bwindmiller at zoonewengland.com]
    Frank Robey

    image

    Student qualifications: programming, familiarity with Linux based computers, and basic knowledge of signal processing techniques. Strong interests in software radio, radio direction finding, ecology, and / or turtles would be helpful.

    Project description: Conservation enables people to understand population dynamics, quantify that conservation efforts are effective, guide decisions about the best use of limited resources, and to intervene directly when necessary. A key aspect of such efforts is the location and tracking of individual animals which is often done using radio identification tags and labor intensive field work. This project seeks to apply advanced radio technology and signal processing techniques to help provide effective radio location of radio tagged animals. We will develop and integrate a sensing system that uses existing radio tags, electromagnetic vector sensors, low cost software radios, low power embedded computers, and battery power systems. Several prototype systems will be implemented and used to perform field measurements to test and validate the signal processing algorithms in real world conditions. This will include a direct collaboration with Zoo New England conservation experts to catalog and track turtle species on the MIT Haystack Observatory property.


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