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Towards Laser Communication Between Cubesats and Drones

Towards Laser Communication Between Cubesats and Drones

Wednesday 02/12/2020
  • Leonid Pogorelyuk
  • Department of Aeronautics and Astronautics,
  • MIT
  • The talk will be given in English

In the upcoming decade, ground-to-space laser links will become abundant in scientific and industrial applications and Unmanned Aerial Vehicles (UAV) will transfer increasingly larger volumes of data. Major companies such as SpaceX and OneWeb will be deploying satellite constellations to provide high data-rate and low-latency communication services, including Free Space Optical (FSO) communication; while smaller-scale cubesat missions are beginning to use lasers as low-mass, high-bandwidth and license-free alternatives to radio communication. FSO links can provide remote sensing UAV with higher data-rates, search and rescue missions with better accessibility, and security-related applications with more reliable connectivity. Combined with satellite constellations, drones also have the potential to provide aerial high-speed internet coverage for remote areas.
Yet, laser communication from Low Earth Orbit (LEO) to small-sized UAV requires several technology demonstrations. Classical optical methods for telescope calibration (using stars) are too slow for rapid attitude estimation, while inertial sensors are not precise enough. A proposed approach to achieving the arcsecond-level precision necessary for signal tracking and acquisition, is to deduce the orientation of the instrument by rapidly processing camera images to identify distant control points. Another challenge associated with airborne telescopes is the turbulence-induced wavefront disturbance. To improve the quality of the signal and reduce transmitter power requirements, wavefront sensing techniques from large stationary observatories need be adapted to low-cost mobile telescopes. This seminar discusses the development and testing of algorithms for high-precision image-based attitude determination and wavefront sensing from vehicles.

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