SPOC

(Spectral Ocean Color Satellite)

Mission Overview

The SPectral Ocean Color (SPOC) satellite mission, was funded through NASA’s second iteration of the Undergraduate Student Instrument Project (USIP) in mid 2016. The SPOC's mission shall acquire moderate resolution imagery across a wide range of spectral bands to monitor coastal ecosystems and ocean color. SPOC will acquire image data between 433 and 866 nm to monitor 1) coastal wetlands status, 2) estuarine water quality including wetland biophysical characteristics and phytoplankton dynamics, and 3) near-coastal ocean productivity. SPOC shall use multispectral remote sensing techniques to quantify vegetation health, primary productivity, ocean productivity, suspended sediments, and organic matter in coastal regions. The uniqueness of SPOC lies in its payload, a 16 band adjustable multi spectral imager, called SPOC eye. The payload structure for SPOC was designed by Cloudland Instruments and the UGA SSRL SPOC team is actively building and refining the optical structure.

Current Status

SPOC was succesfully integrated with NanoRacks on August 19 in Houston. It is scheduled for launch to the ISS on September 29th, 2020 from Wallops, VA. It is part of ELaNa 31 and will be launched onboard the Northrop Grumman Antares rocket (NG-14) as part of a Cygnus resupply mission. Once onboard the ISS SPOC will be deployed into space sometime in late November using the Japanese Experiment Module (JEM) Robotic Manipulator System (JEMRMS). This robotic arm moves aims the satellite below the ISS and releases it.

MOCI:

(Multi-view On-board Computational Imager)

Mission Overview

The Multi-view Onboard Computational Imager (MOCI) mission shall acquire imagery of the Earth’s surface from (Low Earth Orbit) LEO and perform near real time Structure from Motion (SfM) at a landscape scale using custom algorithms and off the shelf, high performance computational units. The MOCI mission will also identify and map coastal phenomena while training students in STEM related fields. Efficient data compression, feature detection, feature matching, and SfM processing techniques of space-based imagery will be performed on board the spacecraft as a proof-of-concept of high performance, on board processing capabilities. 3D models produced by the MOCI satellite will take the form of Digital Surface Models (DSM) as their end product for quick data downlink.

In early 2018 the student team in the UGA SSRL was selected as one of only two winners of the US Air Force Research Laboratory University Nanosatellite Program (Competition NS-9) Flight Selection Review for our MOCI (Multi-view Onboard Computational Imager) spacecraft. The team is now actively building MOCI and is in Phase B of the process.

Launch Information

MOCI is currently in phase B of its construction with an expected delivery date of Q2 2025.

MEMESat-1:

(Mission for Education and Multimedia Engagement Satellite)

Mission Overview

UGA is working with a local nonprofit, Let’s Go to Space, Inc.’s to build its first satellite mission, the Mission for Education and Multimedia Engagement. This spacecraft will be a 1U amateur radio CubeSat. It’s primary mission is to serve as an FM Repeater and to downlink donor submitted memes via UHF SSTV protocol. MEMESat-1 is being created to engage people through outreach and help fund small satellite focused research.

Nearly all systems will be custom build by UGA. Besides serving the greater outreach community this project will help our students hone their skills by allowing them to focus on building subsystems from the ground up.

COSMO:

(Center for Orbital Satellite Mission Operations)

Mission Overview

The Center for Orbital Satellite Mission Operations (COSMO) serves as the communications center for the University of Georgia Small Satellite Research Laboratory (SSRL). COSMO oversees ground station operations from our on-campus rotator installation; along with mission radio support, testing, and implementations.

Currently, COSMO has been working on Ground Station validation and team support for both MOCI and MEMESat-1 through testing and development (radiation pattern testing, GNURadio scripts, and more) !

Broader Interests

Research Interests

The lab is currently focused on advancing

Custom sensors for environmental monitoring
Earth based remote sensing
High performance computational boards utilizing Graphics Processing Units
Feature detection algorithms
Neural networks specifically tailored to classify and track surface based objects
Interconnectivity of multi node systems
Quantum cyber security