In this work we investigate the potential of a thermal infrared (IR) space telescope to remotely characterize the component temperatures of a satellite. With the rapid increase in the number of objects launched in recent years, the ability to detect, track, identify and determine the intent of satellites has become of increasing importance. Spectral modeling of satellites from multi-wavelength photometry in the thermal IR is a technique that has the potential to derive information about the temperature and operational status of a satellite in orbit, without the requirement to spatially resolve the target. Previous work has focused on determination of a single/effective temperature for a Resident Space Objects (RSOs)-such as satellites, asteroids, debris and rocket bodies-from remote observations, obtaining mixed results in terms of ability to classify objects. To progress, we explore a two-greybody component spectral model. Using this analytical model, we investigate which temperature characteristics may be identified from unresolved multi-wavelength photometric observations as a function of the signal-to-noise ratio, under the assumption of Poisson noise-dominated data. With this instrument-agnostic framework, we then quantify the potential of this model to discriminate between RSOs with a single temperature (e.g. natural rocks) versus human-made satellites with a chassis and deployed solar panels where significant component temperature differences exist under typical orbital configurations. Last, we comment on promising prospects of this model for applications to existing and future space telescope observations to characterize RSOs from spatially unresolved photometry. (c) 2025 The Author(s). Published by Elsevier B.V. on behalf of COSPAR. This is an open access article under the CC BY license (http:// creativecommons.org/licenses/by/4.0/).

The increase of ambitions, capabilities and sophistication of small satellite missions highlights the need for efficient payload management to accelerate mission readiness and mitigate risks introduced by system complexities. In this paper we present the architecture for an adaptable instrument control unit designed to interconnect platform and payloads and simplify integration and operation processes. This aims to create a flexible environment for payload designers, enabling them to focus development time on their domain-specific objectives, while the instrument control unit handles the overarching integration, communication, and operational management. We demonstrate the concept of this novel Payload Management System (PMS) as implemented from design to operations in orbit in the SpIRIT nanosatellite mission, launched in December 2023. On SpIRIT, PMS efficiently handles electrical and electronic interfaces between the satellite platform and five diverse payloads developed by four independent stakeholders: a gamma and x-ray telescope, a thermal management system based on a Stirling cycle cooler, a Graphic Processing Unit based edge computing and multi-camera module, an electric propulsion thruster, and an S-band transceiver. The PMS electrical power distribution system includes a supercapacitor bank to supply emergency power to critical payloads. In-orbit performance of this novel functionality is presented and compared to ground tests. PMS contributed to an accelerated development cycle for the mission, and demonstrates the potential for such approach to be replicated in the growing number of nanosatellites equipped with multiple payloads.

The Space Industry Responsive Intelligent Thermal (SpIRIT) 6U CubeSat is a mission led by The University of Melbourne in cooperation with the Italian Space Agency. Launched in a 510 km Polar Sun Synchronous Orbit in December 2023, SpIRIT carries multiple subsystems for scientific and technology demonstration. The main payload is the HERMES instrument for detection of high-energy astrophysics transients (Gamma Ray Bursts), and for studies of their variability at scales below 1 ms. The satellite includes a novel thermal management system for its class, based on a Stirling-cycle cooler and deployable thermal radiator, designed to cool HERMES to reduce instrumental background noise. A low-latency communication subsystem based on a sat-phone network is supporting rapid transmission of time-critical data and telecommands. SpIRIT is also equipped with a set of RGB and thermal IR cameras, connected to an on-board image processing unit with artificial intelligence capabilities for autonomous feature recognition. To effectively manage all interfaces between different subsystems and mission stakeholders, the University of Melbourne developed an instrument control unit (PMS) which operates all payloads. PMS also provides backup uninterruptible power to the HERMES instrument through a supercapacitor-based UPS for safe instrument shutdown in case of platform power interruptions. This paper first presents a mission and payload overview, and early in-orbit results, along with lessons learned throughout the mission. This work not only sheds light on the novelty of some of the on-board technologies onboard and on their potential impact to enable greater utilization of CubeSats for scientific missions, but also offers insights into the practical challenges and accomplishments related to developing and operating a multi-organization CubeSat with a complex array of instruments and systems.

Traditional nanosatellite communication links rely on infrequent ground-station access windows. While this is well suited to both payload data and detailed scheduling information, the resulting long periods without contact are ill-suited for both opportunistic tasking of satellites and triggers generated by autonomous operations. Existing orbital infrastructure in the form of satellite communication (SATCOM) networks, such as Iridium and others provide a readily available and cost effective solution to this problem. While these networks continue to be utilized onboard nanosatellites, a full characterization of their utility and performance in-orbit is vital to understand the reliability and potential for high-timeliness message delivery. The SpIRIT 6U nanosatellite is a mission led by The University of Melbourne in cooperation with the Italian Space Agency and supported by the Australian Space Agency. Developed over the last four years and launched in a 510km Polar Sun Synchronous Orbit in late 2023, SpIRIT carries multiple subsystems for scientific and technology demonstration. The Mercury subsystem provides a demonstration and characterization test bed for SATCOM utilization in-orbit, while also providing the capability of rapid down-link of detection events generated by the main scientific payload of the mission, the HERMES instrument for the detection of high-energy astrophysical transients. This paper first presents a brief payload characterization experiment overview. Early in-orbit results are then presented. This work not only sheds light on the utility of these networks for autonomous operations, and on their potential impact to enable greater utilization of nanosatellites for scientific missions, but also offers insights into the practical challenges related to the design and implementation of utilizing these networks in-orbit.

This paper presents a detailed account of the adaptive AI system deployed on the recently launched SpIRIT nano-satellite. SpIRIT (Space Industry Responsive Intelligent Thermal) is a 6U CubeSat, an Australia-Italy mission led by the University of Melbourne. Launched in December 2023, SpIRIT is equipped with a payload designed to perform advanced computer vision experiments. The nano-satellite was launched with a pre-trained model for cloud detection, featuring the ability for onboard in-orbit fine-tuning. This paper highlights the software and system design choices made to address the unique challenges of running AI in space. The system is engineered for autonomy, robustness, and fault tolerance, allowing it to operate under the extreme conditions of space, including limited power, restricted communications, domain shifts, and constrained computing resources. The system consists of two distinct subsystems: one designed for space operations and the other for Earth-based activities. The space-bound subsystem handles inference and onboard fine-tuning of the model, while the Earth-based subsystem provides oversight and manages ground-truth labeling through a custom-built software called the Ground Truth Factory.

The Thermal Management Integrated System (TheMIS) is a key element of the Australia-Italy Space Industry Responsive Intelligent Thermal (SpIRIT) mission, launched in a 510km Polar Sun-Synchronous orbit in December 2023. SpIRIT is a 6U CubeSat led by The University of Melbourne in cooperation with ASI, with support from ASA and with contributions from Australian space industry and international research organizations. The TheMIS subsystem actively cools and controls the temperature of sensitive instruments, increasing the potential range of payloads supported on small spacecraft systems. TheMIS core functionality is based on a commercial Stirling Cycle Cryocooler in-principle capable of reaching cold-tip temperatures below T=100K. The cooler is operated by customized control electronics and is connected to deployable radiators through pyrolytic graphite sheet thermal straps, all developed by the University of Melbourne. Until now, this level of thermal control has been relatively uncommon in nanosatellites. TheMIS aims to validate the design and performance by controlling the thermal environment of SpIRIT's HERMES payload, an X-ray instrument provided by ASI which has a noise background strongly sensitive to temperature. Beyond SpIRIT, TheMIS has the potential to support a broad range of applications, including holding infrared focal plane arrays at cryogenic temperatures, and increasing resilience of electronics to space weather. This paper provides an overview of TheMIS's design, implementation, and operational performance, detailing the commissioning phase and the early results obtained from its operations in orbit, with comparison to the thermal model developed during the mission environmental testing campaign. Finally, the paper discusses ongoing challenges for thermal management of payloads in small satellite systems and potential future strategies for continuous improvement

Artificial intelligence (AI) and autonomous edge computing in space are emerging areas of interest to augment capabilities of nanosatellites, where modern sensors generate orders of magnitude more data than can typically be transmitted to mission control. Here, we present the hardware and software design of an onboard AI subsystem hosted on SpIRIT. The system is optimised for on-board computer vision experiments based on visible light and long wave infrared cameras. This paper highlights the key design choices made to maximise the robustness of the system in harsh space conditions, and their motivation relative to key mission requirements, such as limited compute resources, resilience to cosmic radiation, extreme temperature variations, distribution shifts, and very low transmission bandwidths. The payload, called Loris, consists of six visible light cameras, three infrared cameras, a camera control board and a Graphics Processing Unit (GPU) system-on-module. Loris enables the execution of AI models with on-orbit fine-tuning as well as a next-generation image compression algorithm, including progressive coding. This innovative approach not only enhances the data processing capabilities of nanosatellites but also lays the groundwork for broader applications to remote sensing from space.

The Space Industry Responsive Intelligent Thermal (SpIRIT) 6U CubeSat nano-satellite is an Australian mission with Italian partecipation for high-energy astrophysics. The 6U CubeSat carries an actively cooled detector system payload in a Sun-synchronous orbit. This payload unit is identical to the six that will fly onboard the High Energy Rapid Modular Ensemble of Satellites (HERMES) Technologic and Scientific Pathfinder ASI mission, hosting compact and innovative X-ray and gamma-ray detector for high energy transients localization (e.g., GRBs). SpIRIT was successfully launched on December 1, 2023 with a SpaceX Falcon 9, and the payload commissioning is in progress and about to be completed. This paper will provide an overview of the SpIRIT scientific payload early orbital operations, with the commissioning and in-flight calibrations of the instrument.

Cubesats and similarly scaled nano-satellites present significant opportunities for hosting both scientific and commercial payloads for Earth sensing and astronomical observations, in particular in the area of rapid-response observations to external triggers. However, one limiting factor to full exploitation of the CubeSat potential in this area lies in the traditional approach of ground-spacecraft communications, which is based on infrequent contact via a limited network of ground stations. An alternative is to leverage existing commercial machine-to-machine orbital networks to transmit the triggers in near-real-time. Here, we present an analysis framework for calculating the likelihood of a time to first contact and the length of contact under minimum guaranteed conditions for these networks. The analysis is then extended to likely operational conditions in orbit, and the results of a comparative trade study of a number of orbital networks are presented, with an emphasis on the applicability to the SkyHopper Space Telescope CubeSat, a nanosatellite astronomical observatory currently undergoing preliminary design. It was found that near-real- time telecommands could be transmitted to SkyHopper within 10min with a likelihood of 62% using the Globalstar network, or a likelihood of 74% using the Iridium network, under predicted nominal operational conditions in orbit. Future networks currently under development could improve these figures to reach greater than 98% coverage with a one second latency.