Phoenix: A CubeSat Mission to Study the Impact of Urban Heat Islands Within the U.S.

Phoenix is a student-led CubeSat mission, developed at Arizona State University (ASU), to study the effects of Urban Heat Islands in several U.S. cities through infrared remote sensing and educate students on space mission design. The spacecraft is designed using commercial off-the-shelf components (COTS) and several custom support boards developed by the student team. As such, the student team was responsible for the design, test, and validation of the spacecraft to demonstrate the capability of using COTS hardware to conduct high-fidelity science. This paper details the mission’s concept of operations, as well as the spacecraft and ground system design that was developed to complete the mission objective. In addition, it details the mission’s current status now that Phoenix has entered the operations phase, along with resources which have proved beneficial to the team while working with the spacecraft in orbit

Dynamically Controlling Image Integration Onboard the Star-Planet Activity Research CubeSat (SPARCS)

The Star-Planet Activity Research CubeSat (SPARCS) is a 6U CubeSat astronomical observatory underdevelopment and will be entirely dedicated to the photometric monitoring of the flaring activity of M dwarfs at near-UV (258 nm – 308 nm) and far-UV (153 nm–171 nm) wavelengths. The SPARCS science pay load is composed of a 9-cm telescope that projects a 40’ field-of-view onto two UV-optimized delta-doped charge-coupled devices (CCDs), which are controlled by a dedicated payload processor board. Given that M dwarf flares in the UV are expected to be capable of reaching amplitudes ∼14,000 times above their quiescent flux, with durations that can be as short as a couple of minutes, the SPARCS payload processor is designed to be able to dynamically adjust the imaging system’s integration times and gains on the fly to reduce CCD pixel saturation issues when flaring events are detected. The SPARCS payload processor is a BeagleBone Black (BBB) with a protective Pumpkin Motherboard Module 2, and runs a custom fully Python-based software to perform active detector thermal control, manage science observations, and apply near-real time image processing to autonomously adjust the exposure times and gains of the detectors upon flare detection. Here we present the approach adopted for that automated dynamic exposure control, as well as its pre-flight tests and performance using simulated M dwarf light curves and full-frame images in the two SPARCS passbands