Explore the vast range of titles available.

The JANUS instrument (Jovis, Amorum ac Natorum Undique Scrutator) aboard the JUpiter ICy moons Explorer (JUICE) is a multispectral camera enabling imaging in the 380-1080 nm wavelength range. The performance and capability of JANUS fulfils all requirements for imaging the variety of different targets JUICE will investigate, including the icy satellites, Io, small inner and irregular moons, the rings and Jupiter itself. JUICE’s orbital trajectory in the Jupiter system will allow icy Galilean satellites observations from afar to closest approaches of a few hundred kilometres, resulting in spatial sampling from km/pixel down to 3 m/pixel respectively. All other targets will be observed from a distance > several 10 5  km , i.e. spatial sampling above several km/pixel. Thirteen bandpass filters provide good spectral coverage with bandwidths from several tens of nm down to 10 nm. The spectral resolution of JANUS will provide unprecedented characterization of endogenic and exogenic geological processes that shaped the icy satellites surfaces, enable monitoring of volcanic activity on Io, and enable investigation of the physical and dynamical properties of small satellites and rings. The dynamics of Jupiter’s atmosphere will be characterised over more than three years at different altitudes thanks to the ad-hoc selected filters. This paper briefly summarizes the science objectives of JANUS and describes in some detail the instrument architecture, its design, performances and observational capabilities. Although specific aspects, like e.g. data calibration, will be covered in future papers, this work is aimed at offering a general reference to the science enabled by JANUS and the design and capabilities of the instrument.

Space-based radar sensors have transformed Earth observation since their first use by Seasat in 1978. Radar instruments are less affected by daylight or weather conditions than optical counterparts, suitable for continually monitoring the global biosphere. The current trends in synthetic aperture radar (SAR) platform design are distinct from traditional approaches in that miniaturized satellites carrying SAR are launched in multiples to form a SAR constellation. A systems engineering perspective is presented in this paper to track the transitioning of space-based SAR platforms from large satellites to small satellites. Technological advances therein are analyzed in terms of subsystem components, standalone satellites, and satellite constellations. The availability of commercial satellite constellations, ground stations, and launch services together enable real-time SAR observations with unprecedented details, which will help reveal the global biomass and their changes owing to anthropogenic drivers. The possible roles of small satellites in global biospheric monitoring and the subsequent research areas are also discussed.

Constellations of small satellites equipped with synthetic aperture radar (SAR) payloads can realize observations in short time intervals independently from daylight and weather conditions and this technology is now in the early stages of development. This tool would greatly contribute to rapid flood monitoring, which is usually one of the main missions in upcoming plans, but few studies have focused on this potential application and a required observation performance for flood disaster monitoring has been unclear. In this study, we propose an unprecedented method for investigating how flood extents would be temporally and spatially observed with a SAR small-satellite constellation and for evaluating that observation performance via an original index. The virtual experiments of flood monitoring with designed constellations were conducted using two case studies of flood events in Japan. Experimental results showed that a SAR small-satellite constellation with sun-synchronous orbit at 570 km altitude, 30-km swath, 15–30° incidence angle, and 20 satellites can achieve 87% acquisition of cumulative flood extent in total observations. There is a difference between the results of observation performance in two cases because of each flood’s characteristics and a SAR satellite’s observation system, which implies the necessity of individual assessments for various types of rivers.

The main objective of the S-STEP (the Small Synthetic Aperture Radar (SAR) Technology Experimental Project (S-STEP)) mission is developing an 80-kg-class active X-band SAR observation small satellite. For lighter, smaller, better, and cheaper development of the S-STEP system, a new thermal design strategy is essential. Therefore, we proposed a new thermal design strategy in this study. The main features of the proposed thermal design involve the minimization of heater power consumption by optimizing environmental heat fluxes on the satellite, the provision of long-term SAR imaging duration in both right- and left-looking modes, and the use of a lightweight flexible graphite sheet as a thermal interface for some high-power instruments. These features contribute to minimizing the satellite’s mass budget through heater power minimization and achieving on-orbit system performance of S-STEP. The effectiveness of the proposed thermal design was numerically verified by on-orbit thermal analysis of the S-STEP system. In addition, the thermal design on a key payload component and the multifunctional transmit/receive module structure were verified through a space-simulated thermal vacuum test.

Small satellites have limited payload and their attitudes are sometimes difficult to determine from the limited onboard sensors alone. Wrong attitudes lead to inaccurate map projections and measurements that require post-processing correction. In this study, we propose an automated and robust scheme that derives the satellite attitude from its observation images and known satellite position by matching land features from an observed image and from well-registered base-map images. The scheme combines computer vision algorithms (i.e., feature detection, and robust optimization) and geometrical constraints of the satellite observation. Applying the proposed method to UNIFORM-1 observations, which is a 50 kg class small satellite, satellite attitudes were determined with an accuracy of 0.02°, comparable to that of star trackers, if the satellite position is accurately determined. Map-projected images can be generated based on the accurate attitudes. Errors in the satellite position can add systematic errors to derived attitudes. The proposed scheme focuses on determining satellite attitude with feature detection algorithms applying to raw satellite images, unlike image registration studies which register already map-projected images. By delivering accurate attitude determination and map projection, the proposed method can improve the image geometries of small satellites, and thus reveal fine-scale information about the Earth.

This paper describes the application of an evolutionary optimization method to design satellite constellation for continuous regional coverage without intersatellite links. This configuration, called mutual coverage, is related to some technical limitations that exist on small satellite technology. The coverage of the north Algerian seismological network is taken as an example of application. A Multi Objective Genetic Algorithm (MOGA) is used to make a trade-off between the improvement of the coverage rate, the minimization of the total number of satellites and the reduction of the satellites’ altitude. First, some experiments have been performed to find the weight distribution of the fitness function that shows the most significant improvement of the average fitness function. Then, some optimized constellation designs are given for different ranges of altitude and it is shown that the size of the MOGA constellation design is significantly reduced compared to the traditional geometrical design.

On 22 December 2020, HISEA-1, the first C-band SAR small satellite for ocean remote sensing, was launched from the coastal Wenchang launch site. Though small in weight, the images it produced have a high spatial resolution of 1 m and a large observation width of 100 km. The first batch of images obtained within the first week after the launch confirmed the rich information in the data, including sea ice, wind, wave, rip currents, vortexes, ships, and oil film on the sea, as well as landmark buildings. Furthermore, geometric characteristics of sea ice, wind vector, ocean wave parameter, 3D features of buildings, and some air-sea interface phenomena in dark spots could also be detected after relevant processing. All these indicate that HISEA-1 could be a reliable, remarkable, and powerful instrument for observing oceans and lands.

Many regions in developing countries do not have any access to communication networks even though the number of devices connected through the Internet of Things (IoT) is increasing significantly. A small satellite platform could provide global network coverage in low Earth orbit to these remote locations at a low cost. This paper describes the overall mission architecture and the implementation of remote IoT using a 1U volume in 6U CubeSat platform named KITSUNE. In KITSUNE, one of the missions is to leverage IoT for building a network of remote ground sensor terminals (GST) in 11 mostly developing countries. This paper evaluates the capacity and coverage of a satellite-based IoT network for providing remote data-collection services to these countries. The amount of data that could be collected from the GSTs and forwarded accurately to the users determines the actual capacity of the Store and Forward (S&F) mission. Therefore, there are several proposed parameters to estimate this capacity in this study. In addition, these parameters are retrieved from the simulations, ground test results, and on-orbit observations with the KITSUNE satellite. The proposed IoT system, which is composed of the GSTs and IoT subsystem onboard KITSUNE satellite, is determined to be capable of providing valuable information from remote locations. In addition, the collected data are achieved and analyzed to monitor sensory data specific to each country, and it could help to generate prediction profiles as well.

This research proposes a tailored Systems Engineering (SE) design process for the development of Attitude and Orbit Control Systems (AOCS) for small satellites operating in formation. These missions, known as Distributed Spacecraft Missions (DSMs), involve groups of satellites—commonly referred to as satellite constellations—whose primary objective is to maintain controlled relative positioning in three dimensions. In these configurations, each satellite may serve a specific role. For instance, one may act as a navigation reference, while another functions as a communication relay. These roles support synchronized control and ensure mission cohesion. To achieve precise relative positioning, the system must integrate specialized sensors and maintain continuous inter-satellite communication. This capability enables precise navigation across both the space and ground segments, while ensuring high control accuracy. As such, the development of AOCS must be approached as a complex systems challenge, involving the coordinated behavior of multiple autonomous elements working toward a shared mission objective. This study tailors the SE process using the ISO/IEC 15288 standard and incorporates a Model-Based Systems Engineering (MBSE) approach to enhance traceability, consistency, and architectural coherence throughout the system lifecycle. As a result, it proposes a customized SE process for AOCS development that begins in the mission’s conceptual phase and addresses the specific functional and operational demands of formation flying. A conceptual example illustrates the proposed process. It focuses on subsystem coordination, communication needs, and the architecture required to support an AOCS for autonomous satellite formations.

Small satellites play an increasing role in earth observation. This article evaluates different possibilities of utilizing data from Planet’s SkySat and PlanetScope satellites constellations for derivation of digital elevation models. While SkySat provides high resolution image data with a ground sampling distance of up to 50 cm, the PlanetScope constellation consisting of Dove 3U cubesats provide images with a resolution of around 4 m. The PlanetScope acquisition strategy was not designed for stereo acquisitions, but for daily acquisition of nadir viewing imagery. Multiple different products can be acquired by the SkySat satellites: Collects covering an area of usually 12 by 6 km, tri-stereo collects and video products with a framerate of 30 Hz. This study evaluates DSM generation using a Semi-Global Matching from multi date stereo pairs for SkySat and PlanetScope, and the dedicated Video and tri-stereo SkySat acquisitions. DSMs obtained by merging many PlanetScope across track stereo pairs show an normalized median deviation against LiDaR first pulse data of 5.2 meter over diverse landcover at the test sites around the city of Terrassa in Catalonia, Spain. SkySat tri-stereo products with 80 cm resolution reach an NMAD of 1.3 m over Terrassa.