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Mission Concepts

Nucleus was conceived as a payload-agnostic high altitude balloon architecture. In addition, Nucleus should host one or more technical or scientific experiments. These experiments serve as a means to validate the design and architecture while stressing the system in a real-world use case.

List of Experiment Ideas

Stable Imaging Platform / Bus Attitude Control

Active gimbals make for a (power hungry) off-the-shelf solution for image stabilization. For a challenge one could build a gimballed camera mount from scratch.1

A more novel idea would be to control bus attitude. A senior design team from 2017 attempted to do attitude control with a reaction wheel, but I don't think they had a way to dump momentum. A simpler (and more novel) approach would be to use RC aircraft engines or drone motors to actively counteract wind forces. A simpler objective could be using drone propellers for anti-spin control or active ballast weights for anti-rocking control.

Pairs with: On-board Image Processing, Rocket Technology Testbed

Altitude Control

Actively change the ascent or descent rate. For a simpler demonstration, only control the ascent rate. For a challenge, maintain an altitude set point. For a greater challenge, extend the flight duration by controlling altitude.2

Pairs with: Intra-balloon Environment Sensors

Intra-balloon Environment Sensors

Develop a sensor platform to measure environmental conditions (temperature, pressure, humidity) within the balloon from ambient, through filling, and finally through the burst event. Send the data to the main payload storage over a wired or wireless link.

As a stretch goal, instrument the bus with environmental sensors. Compare balloon internal conditions to ambient ones add correlate it with altitude rate of change or burst events.

Pairs with: Altitude Control, Characterize Atmospheric Composition, Model and Test Latex Balloon Burst Conditions

On-board Image Processing

Perform image processing (of any level) on images or video on the payload electronics in flight.3 For an extra challenge, apply any of the following constraints:

  • Payload electronics do not exceed $30.
  • Image processing algorithms have a practical or scientific usebeyond a simple demonstrator.
  • Image processing takes place on an FPGA. Bonus if it occurs in realtime.
  • Image processing includes data fusion with additional sensors orcamera sources.

Pairs with: Stable Imaging Platform / Bus Attitude Control

Real-time Data Transfer

Receive real time telemetry and payload data in flight. For a greater challenge, send commands from a ground station during the flight. For a simple demonstration, send limited health and status telemetry. As a stretch, send rich data (like photos or live video) to a ground station in flight.

Pairs with: Intra-balloon Environment Sensors, Characterize Atmospheric Composition, Characterize Radiation Environment, Altitude Control, Stable Imaging Platform / Bus Attitude Control, Rocket Technology Testbed

Characterize Atmospheric Composition

Measure atmospheric composition along the balloon's ascent. Characterize how composition changes with altitude. For a greater challenge, use multiple flights to see how composition changes with altitude from different geographic locations, time of day, time of year, or different weather conditions.

Pairs with: Altitude Control, Intra-balloon Environment Sensors

Characterize Radiation Environment

Measure radiation intensity along the balloon's ascent. Characterize how intensity changes with altitude. For a greater challenge, use multiple flights to see how intensity changes with altitude from different geographic locations, time of day, time of year, or different weather conditions.

Pairs with: Altitude Control, Intra-balloon Environment Sensors

Model and Test Latex Balloon Burst Conditions

Prior to launch, predict the conditions that lead to the balloon's burst event. Instrument the payload and balloon to test the model in flight. For an extra challenge, apply any of the following constraints:

  • Model the burst event only using parameters that can be measured in flight.
  • Test the model on the ground with simulated atmospheric conditions and a sub- or full-scale balloon.
  • Record high-speed video of the balloon bursting in flight.

Pairs with: Intra-balloon Environment Sensors

Controlled Descent

After balloon cutdown, control the descent of the payload. For a simpler challenge, use a reefed parachute. For a greater challenge, steer the descent path using a parafoil or aero control surfaces.

Pairs with: Rocket Technology Testbed, Advanced Dynamics Modelling

Vegetation Density Experiment

Measure vegetation density using NDVI with cameras in flight. For a greater challenge, do the image processing on-board.4

Pairs with: Stable Imaging Platform / Bus Attitude Control, On-board Image Processing

F' Flight Software Ecosystem

F' (F Prime) is a component-driven framework that enables rapid development and deployment of spaceflight and other embedded software applications.5 F' is part of NASA Jet Propultion Lab's technology ecosystem, open source, and also has demos that are meant to be run on a Raspberry Pi.

F' can be used to create common HAB flight software leveraging existing components. The team will create additional components to meet the needs of specific HABs, with the ability to open source for use by other HAB teams.

  • Run HAB FSW with F' using a one off greedy customization, not going out of the way for code reuse.
  • Design HAB FSW with F' to be common and for use by other HAB teams as a base.
  • Design hardware payloads with accompanying F' components to be common for use by teams that want a plug and play HAB payload.

Pairs with:

Long Distance Communications

Send or receive data to the HAB in flight while it is beyond visual range. For a greater challenge, send or receive data while the HAB is beyond the geographical horizon of the ground station.

Pairs with: Real-time Data Transfer

Multispectral / Hyperspectral Instrument

Image the Earth, sky, or atmospheric limb with a camera sensitive to two or more spectral bands. Optionally apply any of the following constraints:

  • Use components which cost no more than $50.6
  • Calibrate the instrument on the ground (optionally in flight-like conditions)

Pairs with: Stable Imaging Platform / Bus Attitude Control, On-board Image Processing, Vegetation Density Experiment

Star Tracker

Build an instrument that measures position of the payload bus based on optical measurements of the sky.78 Optionally apply any of the following constraints:

  • Use components which cost no more than $50.
  • Calibrate the instrument on the ground (optionally in flight-like conditions)
  • Implement a custom algorithm to derive orientation from images of the sky.

Pairs with: Stable Imaging Platform / Bus Attitude Control, On-board Image Processing

Synthetic Image Quality Enhancement

Use computer vision techniques to improve the effective resolution of images by either of the following methods:

  1. Stitch multiple image frames into a larger composite image of an area wider than the camera's field of view.9
  2. Use multi-frame super-resolution algorithms to create high resolution image products from low resolution images captured in flight.1011

Pairs with: Stable Imaging Platform / Bus Attitude Control, On-board Image Processing

Advanced Dynamics Modelling

Create a dynamics model for the HAB bus that accounts for differential drag bus geometry, variable wind speed and direction, variable ambient pressure, twist and tension from the balloon tether, and the center of gravity of the bus or mass and location of internal components. If attitude control is also under consideration, also model the effects of that control system and simulate its behavior in different situations.

Pairs with: Stable Imaging Platform / Bus Attitude Control, Altitude Control, Controlled Descent, Flight Conditions Characterizer,

Mission Monitoring Ground Station

Monitor telemetry in flight or during tests and display telemetry and other information with an intuitive user interface. For a greater challenge, also implement command and control elements. Examples of UI elements that could be used are:

  • Live-updating plots of telemetry values over time
  • Live-updating log messages from the avionics
  • Live video feeds from cameras on board
  • Command and control interfaces for sending messages to the vehicle

Pairs with: Real-time Data Transfer

Mothership for Smaller Vehicles

Stow smaller vehicles such as tiny quadcopters on the HAB and release them in flight. For a greater challenge, use the HAB as a relay for recording data or sending data from the child vehicles back to Mission Control.

Pairs with: Real-time Data Transfer, Long Distance Communications

Sprawled Small Scale HABs

Design and build a small scale HAB (50 grams) which includes a downward facing camera. The small scale HABs should be able to function for at least a few hours, this includes power on time and storage requirements. Multiple of these small scale HABs will be connected together with lightweight wire or string. The collective HABs can be used to map out the terrain over large distances as connections between individual HABs will be lengthy (maybe 500m - 1km).

Pairs with: Vegetation Density Experiment

Launch Platform

Develop a launch platform system capable of controlling the payload during launch preparations. Includes clamp system to retain payload to the ground during launch preparation. Data/Power/Fueling connections available to interface with the payload. System would allow for hands off approach during setup from filling the balloon to last minute software updates and real time telemetry without relying on onboard radios.

Design can be tiered, for example power and data would be primary goal and fueling cabilities as a stretch goal.

Pairs with: Mission Monitoring Ground Station

Balloon Movement Sensors

Develop a sensor platform to measure inertial movement of balloon (acceleration, rotation, magnetic heading) through full flight of balloon. Send the data to the main payload storage over a wired or wireless link.

Correlate data with similar sensors on the HAB bus to create better stabilization algorithms and control methods.

Pairs with: Stable Imaging Platform / Bus Attitude Control, On-board Image Processing, Intra-balloon Environment Sensors

Reference Missions

This section outlines reference payloads and mission profiles for Nucleus which satisfy the main mission objective of demonstrating the avionics architecture by supporting a combination of technical or scientific experiments.

Vegetation Density Mapper

The spiritual successor to Where U At Plants? and Phil's vision for HAB CV.

Mount at least two ground-facing cameras to the HAB payload. Collect photos or videos of the ground in the Red and Near-Infrared spectral bands as needed to compute NDVI on the ground below. Calibrate spectral response and lens distortion of all payload cameras on the ground before flight.

Experiments (Level I):

  • Vegetation Density Experiment: Record flight data (GPS coordinates, altitude, orientation) in sync with image captures. Use flight data, camera field of view, and image data to project image data onto a map. Flight data and imagery is stored to local memory. All data processing and analysis takes place after flight data is recovered.

Experiments (Level II):

Experiments (Level III):

  • Stable Imaging Platform / Bus Attitude Control: Use active control systems and actuators (reaction mass, ballast, electric motors, thrust) to stabilize the platform where the payload cameras are mounted. In addition to control actuators, pointing knowledge is necessary to feed the control system.

Flight Conditions Characterizer

A knowledge-gathering mission to inform flight characteristics and environments on future HAB flights.

Instrument the HAB bus to measure ambient conditions, internal conditions within the bus structure, and internal conditions within the balloon over a long-duration flight to gain detailed insights into the conditions subjected to the hardware. Calibrate all sensors on the ground in known conditions, ideally with an environmental test chamber, prior to the flight.

Experiments (Level I):

Experiments (Level II):

  • Intra-balloon Environment Sensors: Measure temperature, humidity, pressure and density of helium within the balloon. Also measure detailed thermal gradients throughout the payload bus and components.
  • Real-time Data Transfer: Downlink all or part of the data to a ground station while in flight.
  • Model and Test Latex Balloon Burst Conditions: Model and test (on the ground) the conditions that lead to the balloon's burst event. Instrument the balloon and payload to validate this model and characterize the burst event in detail.

Experiments (Level III):

  • Altitude Control: Maintain flight at certain altitude(s) to gain more data about the conditions at that height in order to smooth out outliers and variations. Optionally extend mission flight time to gain more data.

Flying Robot

A knowledge-building mission that develops key building blocks toward satellite-like operations tasks such as command and control, data links, and ACS systems (like detumbling).

Send commands from a ground station that are executed by the HAB in flight. The HAB reacts to both command instructions and stimuli from its environment.

Experiments (Level I):

  • Real-time Data Transfer: Downlink all or part of the data to a ground station while in flight. Execute commands sent from a ground station and report acknowledgement of a received command to the ground.

Experiments (Level II):

  • Controlled Descent: Automatically detect a free-fall state and use active controls and actuators (parafoil, control surfaces) to change the speed and direction of descent. Descent should be controlled in a way that makes recovery of the payload easier.

Experiments (Level III):

  • Altitude Control: Maintain a set altitude in flight and change the altitude set point in response to a command from the ground station.
  • Stable Imaging Platform / Bus Attitude Control: Maintain a set attitude (of the imaging platform) and change the target attitude in response to a command from the ground station.

Rocket Technology Testbed

A technology demonstration mission for key technologies meant for use with rockets.

Develop avionics, logic, and other foundational technologies for controls, telemetry, and ground stations using requirements based on what would be used in an M-class hobby rocket. Select experiments that can be demonstrated on a HAB and easily adapted for flight in a rocket.

Experiments (Level I):

Experiments (Level II):

  • Controlled Descent: Automatically detect a free-fall state and use active controls and actuators (parafoil, control surfaces) to change the speed and direction of descent. Descent should be controlled in a way that makes recovery of the payload easier.
  • Advanced Dynamics Modelling: Model the dynamics of the flight and validate the model with flight data.

Experiments (Level III):

  • Stable Imaging Platform / Bus Attitude Control: Use active control systems and actuators (reaction mass, ballast, control surfaces, or thrust) to stabilize the roll axis (the axis along the balloon tension line) during ascent and/or descent. In addition to control actuators, pointing knowledge is necessary to feed the control system. Special preference should be given to propulsive systems or aero control surfaces that could also be adapted for use during a rocket's ascent phase.

  1. Haumpton, Shane. 2018. How to create a DIY gimbal stabilizer. DIY Photography. ↩

  2. Sushko, Audrey, et. al. 2017. Low Cost, High Endurance, Altitude-Controlled Latex Balloon for Near-Space Research (ValBal). Standford Space Initiative. ↩

  3. Linden, Philip, et. al. 2018. On-Board Image Processing and Computer Vision Techniques on Low-Cost Consumer Electronics for Vegetation Density Mapping and Other Experiments. RIT Space Exploration. ↩

  4. Linden, Philip. 2018. Where U At Plants? (WUAP): Capturing and Masking Images from Raspberry Pi 3 + Pi Camera. RIT Space Exploration. ↩

  5. NASA Jet Propulsion Lab. 2020. F´: A Flight-Proven, Multi-Platform, Open-Source Flight Software Framework. GitHub. ↩

  6. Sigernes, Fred, et. al.. 2018. Do it yourself hyperspectral imager for handheld to airborne operations. Optics Express. ↩

  7. McBryde, Christopher Ryan. 2012. A star tracker design for CubeSats. University of Texas at Austin. ↩

  8. Smith, Casey Grant. 2017. Development and implementation of star tracker based attitude determination. Missouri University of Science and Technology. ↩

  9. Szeliski, Richard. 2006. Image Alignment and Stitching: A Tutorial. Foundations and Trends in Computer Graphics and Vision. ↩

  10. Nelson, Kyle, et. al. 2012. Performance Evaluation of Multi-Frame Super-Resolution Algorithms. IEEE. ↩

  11. Farsiu, Sina, et. al. 2004. Fast and robust multiframe super resolution. IEEE. ↩