Thanks to advancements in silicon photomultiplier sensors (SiPMs) and system-on-chip (SoC) technology, our INFN Roma1 group developed ArduSiPM in 2012, the first all-in-one scintillator particle detector in the literature. It used a custom Arduino Due shield to process fast signals, utilizing the Microchip Sam3X8E SoC\'s internal peripherals to control and acquire SiPM signals. The availability of radiation-tolerant SoCs, combined with the goal of reducing system space and weight, led to the development of an innovative second-generation board, a better-performing device called Cosmo ArduSiPM, suitable for space missions. The architecture of the new detector is based on the Microchip SAMV71 300 MHz, 32-bit ARM® Cortex®-M7 (Microchip Technology Inc., Chandler, AZ, USA). While the analog front-end is essentially identical to the ArduSiPM, it utilizes components with the smallest possible package. The board fits in a CubeSat module. Thanks to the compact design, the board has two independent channels, with a total weight of only 40 grams within a CubeSat form factor. The ArduSiPM architecture is based on a single microcontroller and fast discrete analog electronics. It benefits from the continued development of SoCs related to the IoT (Internet of Things) market. Compared with a system with a custom ASIC, this architecture based on software and SoC capabilities offers considerable advantages in terms of cost and development time. The ability to incorporate new commercial SoCs, continuously emerging from advancements in the aerospace and automotive industries, provides the system with a robust foundation for sustained growth over the years. A detailed characterization of the hardware and the system\'s response to different photon fluxes is presented in this article. Additionally, coupling the device with a scintillator was tested at the end of this article as a preliminary trial for future measurements, showing potential for further enhancement of the detector\'s capabilities.

CubeSats have emerged as cost-effective platforms for biological research in low Earth orbit (LEO). However, they have traditionally been limited to optical absorbance sensors for studying microbial growth. This work has made improvements to the sensing capabilities of these small satellites by incorporating electrochemical ion-selective pH and pNa sensors with optical absorbance sensors to enrich biological experimentation and greatly expand the capabilities of these payloads. We have designed, built, and tested a multi-modal multi-array electrochemical-optical sensor module and its ancillary systems, including a fluidic card and an on-board payload computer with custom firmware. Laboratory tests showed that the module could endure high flow rates (1 mL/min) without leakage, and the 27-well, 81-electrode sensor card accurately detected pH (71.0 mV/pH), sodium ion concentration (75.2 mV/pNa), and absorbance (0.067 AU), with the sensors demonstrating precise linear responses (R2 ≈ 0.99) in various test solutions. The successful development and integration of this technology conclude that CubeSat bio-payloads are now poised for more complex and detailed investigations of biological phenomena in space, marking a significant enhancement of small-satellite research capabilities.

In the context of Kalman filters, the predicted error covariance matrix Pk+1 and measurement noise covariance matrix R are used to represent the uncertainty of state variables and measurement noise, respectively. However, in real-world situations, these matrices may vary with time due to measurement faults. To address this issue in CubeSat attitude estimation, an adaptive extended Kalman filter has been proposed that can dynamically estimate the predicted error covariance matrix and measurement noise covariance matrix using an expectation-maximization approach. Simulation experiments have shown that this algorithm outperforms existing methods in terms of attitude estimation accuracy, particularly in sunlit and shadowed phases of the orbit, with the same filtering parameters and initial conditions.

Prompt attitude stabilization is more challenging in Nano CubeSat due to its minimal capacity, weight, energy, and volume-constrained architecture. Fixed gain non-adaptive classical proportional integral derivative control methodology is ineffective to provide optimal attitude stability in low earth orbit under significant environmental disturbances. Therefore, an artificial neural network with fuzzy inference design is developed in a simulation environment to control the angular velocity and quaternions of a CubeSat by autonomous gain tuning of the proportional-derivative controller according to space perturbations. It elucidates the dynamics and kinematics of the CubeSat attitude model with reaction wheels and low earth orbit disruptions, i.e., gravity gradient torque, atmospheric torque, solar radiation torque, and residual magnetic torque. The effectiveness of the proposed ANFIS-PD control scheme shows that the CubeSat retained the three-axis attitude controllability based on initial quaternions, the moment of inertia, Euler angle error, attitude angular rate, angular velocity rate as compared to PID, ANN, and RNN methodologies. Outcomes from the simulation indicated that the proposed controller scheme achieved minimum root mean square errors that lead towards rapid stability in roll, pitch, and yaw axis respectively within 20 s of simulation time.

This study introduces a prototype end-to-end Simulator software tool for simulating two-dimensional satellite multispectral imagery for a variety of satellite instrument models in aquatic environments. Using case studies, the impact of variable sensor configurations on the performance of value-added products for challenging applications, such as coral reefs and cyanobacterial algal blooms, is assessed. This demonstrates how decisions regarding satellite sensor design, driven by cost constraints, directly influence the quality of value-added remote sensing products. Furthermore, the Simulator is used to identify situations where retrieval algorithms require further parameterization before application to unsimulated satellite data, where error sources cannot always be identified or isolated. The application of the Simulator can verify whether a given instrument design meets the performance requirements of end-users before build and launch, critically allowing for the justification of the cost and specifications for planned and future sensors. It is hoped that the Simulator will enable engineers and scientists to understand important design trade-offs in phase 0/A studies easily, quickly, reliably, and accurately in future Earth observation satellites and systems.

Greenhouse gases absorb the Earth\'s thermal radiation and partially return it to the Earth\'s surface. When accumulated in the atmosphere, greenhouse gases lead to an increase in the average global air temperature and, as a result, climate change. In this paper, an approach to measuring CO2 and CH4 concentrations using Fourier transform infrared spectroscopy (FTIR) is proposed. An FTIR spectrometer mockup, operating in the wavelength range from 1.0 to 1.7 μm with a spectral resolution of 10 cm-1, is described. The results of CO2 and CH4 observations throughout a day in urban conditions are presented. A low-resolution FTIR spectrometer for the 16U CubeSat spacecraft is described. The FTIR spectrometer has a 2.0-2.4 μm spectral range for CO2 and CH4 bands, a 0.75-0.80 μm range for reference O2 bands, an input field of view of 10-2 rad and a spectral resolution of 2 cm-1. The capabilities of the 16U CubeSat spacecraft for remote sensing of greenhouse gas emissions using a developed FTIR spectrometer are discussed. The design of a 16U CubeSat spacecraft equipped with a compact, low-resolution FTIR spectrometer is presented.

CubeSats require accurate determination of their orientation relative to the Sun, Earth, and other celestial bodies to operate successfully and collect scientific data. This paper presents an orientation system based on solar and magnetic sensors that offers a cost-effective and reliable solution for CubeSat navigation. Solar sensors analyze the illumination on each face to measure the satellite\'s orientation relative to the Sun, while magnetic sensors determine the Earth\'s magnetic field vector in the satellite\'s reference frame. By combining the measured data with the known ephemeris of the satellite, the satellite-Sun vector and the magnetic field orientation can be reconstructed. The orientation is expressed using quaternions, representing the rotation from the internal reference system of the satellite to the selected reference system. The proposed system demonstrates the ability to accurately determine the orientation of a CubeSat using only two sensors, making it suitable for installations where more complex and expensive instruments are impractical. Additionally, the paper presents a mathematical model of a low-cost CubeSat orientation system and a hardware implementation of the sensor. The technology, using solar and magnetic sensors, provides a reliable and affordable solution for CubeSat navigation, supporting the increasing sophistication of miniature payloads and enabling accurate satellite positioning in space missions.

This article presents a multi-band right-hand circularly polarized antenna designed for the Cube Satellite (CubeSat). Based on a quadrifilar structure, the antenna provides circular polarization radiation suitable for satellite communication. Moreover, the antenna is designed and fabricated using two 1.6 mm thickness FR4-Epoxy boards connected by metal pins. In order to improve the robustness, a ceramic spacer is placed in the centerboard, and four screws are added at the corners to fix the antenna to the CubeSat structure. These additional parts reduce antenna damage caused by vibrations in the launch vehicle lift-off stage. The proposal has a dimension of 77 × 77 × 10 mm3 and covers the LoRa frequency bands at 868 MHz, 915 MHz, and 923 MHz. According to the measurements in the anechoic chamber, antenna gains with the values of 2.3 dBic and 1.1 dBic are obtained for the 870 MHz and 920 MHz, respectively. Finally, the antenna is integrated into a 3U CubeSat that was launched by a Soyuz launch vehicle in September 2020. The terrestrial-to-space communication link was measured, and the antenna performance was confirmed in a real-life scenario.

Plant phenology describes the timing of reproductive events including flowering and fruiting, which for many species are affected by fire disturbance. Understanding phenological responses to fire provides insights into how forest demographics and resources may shift alongside increasing fire frequency and intensity driven by climate change. However, isolating the direct effects of fire on a species\' phenology and excluding potential confounders (e.g. climate, soil) has been difficult due to the logistical challenges of monitoring species-specific phenological events across myriad fire and environmental conditions. Here, we use CubeSat-derived crown-scale flowering data to estimate the effects of fire history (time since fire and fire severity over a 15-year time span) on flowering of the eucalypt Corymbia calophylla across a Mediterranean-climate forest (814km2) in southwest Australia. We found that fire reduced the proportion of flowering trees at the landscape-scale, and flowering recovered at a rate of 0.15 % (±0.11% SE) per year. Further, this negative effect was significant due to high crown scorch fires (>20% canopy scorch), yet there was no significant effect from understory burns. Estimates were obtained using a quasi-experimental design which identifies the effect of time since fire and severity on flowering by comparing proportional flowering within target fire perimeters (treatment) and adjacent past fire perimeters (control). Given the majority of fires studied were managed fuel reduction burns, we applied the estimates to hypothetical fire regimes to compare flowering outcomes under more or less frequent prescribed burning. This research demonstrates the landscape-scale effects of burning on a tree species\' reproduction, which could broadly impact forest resiliency and biodiversity.

With the imminent human exploration of deep space, it is more important than ever to understand the biological risks of deep space radiation exposure. The BioSentinel mission will be the first biological payload to study the effects of radiation beyond low Earth orbit in 50 years. This study is the last in a collection of articles about the BioSentinel biological CubeSat mission, where budding yeast cells will be used to investigate the response of a biological organism to long-term, low-dose deep space radiation. In this study, we define the methodology for detecting the biological response to space-like radiation using simulated deep space radiation and a metabolic indicator dye reduction assay. We show that there is a dose-dependent decrease in yeast cell growth and metabolism in response to space-like radiation, and this effect is significantly more pronounced in a strain of yeast that is deficient in DNA damage repair (rad51Δ) compared with a wild-type strain. Furthermore, we demonstrate the use of flight-like instrumentation after exposure to space-like ionizing radiation. Our findings will inform the development of novel and improved biosensors and technologies for future missions to deep space.