Sporadic ocean color events with characteristic spectra, in particular algal blooms, call for quick delivery of high-resolution remote sensing data for further analysis. Motivated by this, we present the mission design for HYPerspectral Smallsat for Ocean observation (HYPSO-1), a 6U CubeSat at 500 km orbital altitude hosting a custom-built pushbroom hyperspectral imager with wavelengths 387–801 nm at 3.33 nm bandpass and a swath width of 70 km. The imager’s expected signal-to-noise ratio is characterized for typical open ocean water-leaving radiance which can be flexibly increased by binning pixels. Using geometric principles, the satellite shall execute a slew maneuver during a scan to induce greater overlap in the pixels with a goal to enable better than 100 m spatial resolution. Since high-dimensional hyperspectral data need to be transmitted over limited space-to-ground communications, we have designed a modular FPGA-based onboard image processing architecture that significantly reduces the data size without losing important spatial-spectral information. We justify the concept with a simulated scenario where HYPSO-1 first collects numerous hyperspectral images of a 40 km by 40 km coastal area in Norway and aims to immediately transfer these to nearby ground stations. Using CCSDS123 lossless compression, it takes about one orbital revolution to obtain the complete data product when considering overhead in satellite bus communications and less than 10 min without the overhead. It is shown that even better latency can be achieved with more advanced onboard processing algorithms.

The HYPSO-1 satellite, a 6U CubeSat carrying a hyperspectral imager, was launched on 13 January 2022, with the Goal of imaging ocean color in support of marine research. This article describes the development and current status of the mission and payload operations, including examples of agile planning, captures with low revisit time and time series acquired during a campaign. The in-orbit performance of the hyperspectral instrument is also characterized. The usable spectral range of the instrument is in the range of 430 nm to 800 nm over 120 bands after binning during nominal captures. The spatial resolvability is found empirically to be below 2.2 pixels in terms of Full-Width at Half-Maximum (FWHM) at 565 nm. This measure corresponds to an inherent ground resolvable resolution of 142 m across-track for close to nadir capture. In the across-track direction, there are 1216 pixels available, which gives a swath width of 70 km. However, the 684 center pixels are used for nominal captures. With the nominal pixels used in the across-track direction, the nadir swath-width is 40 km. The spectral resolution in terms of FWHM is estimated to be close to 5 nm at the center wavelength of 600 nm, and the Signal-to-Noise Ratio (SNR) is evaluated to be greater than 300 at 450 nm to 500 nm for Top-of-Atmosphere (ToA) signals. Examples of images from the first months of operations are also shown.

Hyperspectral imaging is a powerful remote sensing technology, but its use in space is limited by the large volume of data it produces, which leads to a downlink bottleneck. Therefore, most payloads to date have been oriented towards demonstrating the scientific usefulness of hyperspectral data sporadically over diverse areas rather than detailed monitoring of spatio-spectral dynamics. The key to overcoming the data bandwidth limitation is to process the data on-board the satellite prior to downlink. In this article, the design, implementation, and in-flight demonstration of the on-board processing pipeline of the HYPSO-1 cube-satellite are presented. The pipeline provides not only flexible image processing but also reliability and resilience, characterized by robust booting and updating procedures. The processing time and compression rate of the simplest pipeline, which includes capturing, binning, and compressing the image, are analyzed in detail. Based on these analyses, the implications of the pipeline performance on HYPSO-1’s mission are discussed.

Traditional large Earth Observation Satellites (EOS) are designed with simple imaging strategies. However, small satellites can satisfy immediate user needs through agile imaging modes. In this paper, we model several agile imaging mode concepts and test them experimentally on the push-broom hyperspectral imaging cubesat HYPSO-1. Six imaging modes are tested: slewing, multi-target, dual-angle, wide swath, on-board processing, and dynamic pointing. The results show that the slewing and multi-angle mode increased estimated Signal-to-Noise Ratio (SNR) by 1.4x to 1.7x, the on-board processing mode decreased data latency, and the multi-target, wide swath and dynamic pointing modes enhanced spatial coverage.

Digital engineering is increasingly introduced for managing and supporting the development of systems for space. However, few academic teams have the competency needed to manage projects using digi...

Assembly, Integration, and Verification/Testing (AIV or AIT) is a standardized guideline for projects to ensure consistency throughout spacecraft development phases. The goal of establishing such a guideline is to assist in planning and executing a successful mission. While AIV campaigns can help reduce risk, they can also take years to complete and be prohibitively costly for smaller new space programs, such as university CubeSat teams. This manuscript outlines a strategic approach to the traditional space industry AIV campaign through demonstration with a 6U CubeSat mission. The HYPerspectral Smallsat for Ocean observation (HYPSO-1) mission was developed by the Norwegian University of Science and Technology’s (NTNU) SmallSatellite Laboratory in conjunction with NanoAvionics (the platform provider). The approach retains critical milestones of traditional AIV, outlines tailored testing procedures for the custom-built hyperspectral imager, and provides suggestions for faster development. A critical discussion of de-risking and design-driving decisions, such as imager configuration and machining custom parts, highlights the consequences that helped, or alternatively hindered, development timelines. This AIV approach has proven key for HYPSO-1’s success, defining further development within the lab (e.g., already with the second-generation, HYPSO-2), and can be scaled to other small spacecraft programs throughout the new space industry.