Advanced Cubesat Imaging Payload

Bob Urberger (facilitator), Joe Mayer, and Nathan Bossart | Engineering Senior Design - ECE 491 - Electrical and Computer Engineering

Project Abstract

Modern spacecraft have demanding imaging requirements and little space or power to work with. A wide variety of visual data, including IR, visible spectrum and UV can be used to provide the necessary situational awareness to recognize debris or potential threats and to faciliate close range operations, such as docking two spacecraft.

Imaging systems for modern spacecraft are typically very expensive and bulky, incorporating large cooled thernal cameras and complex optics and consuming large amounts of power to gather visual data, most of which is useless images of deep space. In order to identify potential threats, the spacecraft requires basic object recognition at a minimal distance (withing 1 km) and reasonable recognition accuracy for close range maneuver operations. These are achievable with relatively cheap hardware, all of which can be operated in a small form factor suitable for cubesats at a reasonable power budget.

This project will build off of the Space Systems Research Lab's current imager payload, redesigning it for more advanced capabilities. It will require a custom built thermally regulated CMOS imager, an ARM processor for general flow control, and an FPGA to offload high-throughput computation and custom hardware control. The system will be capable of basic image processing, including object identification, distance detection, and classification of properly marked faces (with LED patterns) of a Cubesat spacecraft.

In addition to direct application to the payload of the Space Systems Research Lab's RASCAL mission, this system could be useful to any aerospace corporation building small Cubesats or small to medium scale satellites which require imaging payloads for object and azimuth identification of other spacecraft.

Click here for a more detailed project description.
Click here for a list of project references.

Last Updated 4/18/14