NanoEOAP Spacecraft

Two main payloads: (i) a particle detector and (ii) a 6-channel multispectral camera. 

The satellite has two main different payloads: (i) a particle detector and (ii) a 6-channel multispectral camera.

The particle detector is a hodoscope consisting of two deployable plastic scintillators separated by 25 cm along principal axis of the satellite, optically connected to Silicon photomultipliers (SiPM). The front-end electronics is based on a SoC-FPGA and can operate either in counting or integration mode. The particle detector will measure the directional flux of high energy electrons and protons trapped in the magnetosphere at L-shells with 1.07 ≤ L ≤ 5, with an angular resolution of ∆Ω? = 0.4 str for energies in the range 100keV ≤ E ≤ 1GeV . These particles can be solar and originated in space weather events or low energy galactic cosmic rays. Besides this primary objective, the detector will be pathfinder for astrophysical gamma ray detection. The detector has been developed at LINX and is also a pathfinder of SiPM utilization in space for the proposed Extreme University Space Observatory (JEMEUSO) for ultra-high energy cosmic ray detection.

The multispectral camera, on the other hand, has a spatial resolution (GSD at 500 km) of 16 m (PAN) and 32 m (MS) for a swath of 32 km. The camera will map the Mexican territory and is a pathfinder for a larger EO low-cost constellation for application in climate change assessment and mitigation, sustainable use of water resources, deforestation characterization and the effects of urban contamination on mangrove forests.

The satellite has a 3U CubeSat standard format with deployable solar panels and UHF antennas. The hodoscope particle detector has two independent deployable structures which move de scintillators outside the main mechanical structure of the satellite to avoid undesirable attenuation by other subsystems, and insulate the scintillators from Oxygen attack.

The satellite works on UHF-band (up and down link) and S-band (downlink). The satellite will incorporate onboard AI to efficiently administer its actual resources in real time, maximizing data download and improving performance in general by optimizing scientific task scheduling.