FSSCat: The Federated Satellite Systems <sup>3</sup>Cat Mission: Demonstrating the capabilities of CubeSats to monitor essential climate variables of the water cycle [Instruments and Missions]

Camps, A.; Muñoz-Martín, Joan Francesc; Ruiz-de-Azua, Joan A.; Fernández, Lara P.; Perez-Portero, A.; Llaveria, David; Herbert, Christoph; Pablos, Míriam; Golkar, Alessandro; Gutierrez, Antonio P.; Antônio, Carlos; Bandeiras, Jorge; Andrade, Jorge; Cordeiro, D.; Briatore, Simone; Garzaniti, Nicola; Nichele, Fabio; Mozzillo, Raffaele; Piumatti, A.; Cardi, Margherita; Esposito, Marco; Dijk, Chris van; Vercruyssen, Nathan; Barbosa, João Roberto; Hefele, John; Koeleman, Rick; Domínguez, Bernardo Carnicero; Pastena, Massimiliano; Filippazzo, Giancarlo; Reagan, Amanda

doi:10.1109/mgrs.2022.3219778

Cited by 16 publications

(5 citation statements)

References 17 publications

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“…Additionally, the second CubeSat included Cosine's HyperScout-2 visible + nearinfrared + thermal infrared hyperspectral imager and included the PhiSat-1 AI board in a Movidius processor. Notably, FSSCat was the first CubeSat-based mission that contributed to the Copernicus program [161]. The application of AI in CubeSat missions has revolutionized the efficiency and accuracy of data processing.…”

Section: Satellite Technology Breakthroughs: 2019-2020 Achievements A...mentioning

confidence: 99%

Considerations for Eco-LeanSat Satellite Manufacturing and Recycling

Buitrago-Leiva,

Camps,

Moncada Niño

2024

Sustainability

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This research aims to contribute to the development of the Eco-LeanSat concept by focusing on a sustainable approach to satellite manufacturing and the repurposing of remaining satellite capabilities after failure. Despite satellites no longer being suitable for their original purposes, these remaining capabilities can find new applications. The study begins by identifying relevant innovative eco-design applications. Subsequently, it examines sustainability within the satellite lifecycle supply chain, categorizing it into four methods: (1) active debris removal, (2) transport logistics, (3) mission extension, and (4) repair and construction. Aligned with emerging trends in space activities, the study also considers future developments to maximize satellites’ potential to provide new services. Additionally, the research includes a description of a potential lean manufacturing process that encompasses logistic chains to support the development of a more sustainable space economy. Finally, the study concludes with a technological survey tracing the evolution of the development of the SmallSat and CubeSat platforms that identifies relevant innovative designs for a sustainable space environment.

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Section: Satellite Technology Breakthroughs: 2019-2020 Achievements A...mentioning

confidence: 99%

Considerations for Eco-LeanSat Satellite Manufacturing and Recycling

Buitrago-Leiva,

Camps,

Moncada Niño

2024

Sustainability

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“…In addition, hyperspectral imagers have become nowadays small enough that they can even be fit in CubeSats. Examples of these sensors are the HyperScape50 or HyperScape100 from Simera Sense [1], and the HyperScout 2 from Cosine [2] that flew onboard the FSSCat mission [3].…”

Section: Introductionmentioning

confidence: 99%

Efficient Onboard Band Selection Algorithm for Hyperspectral Imagery in SmallSat Missions With Limited Downlink Capabilities

Llaveria,

Park,

Camps

et al. 2024

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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Hyperspectral imaging is a key tool in numerous remote sensing applications. Images with tens or even hundreds of spectral bands contain a wealth of information to retrieve multiple geophysical parameters, to perform target detection, or land classification with unbeatable high accuracies. In addition, hyperspectral sensors are becoming smaller, and today they even fit in CubeSats. However, the amount of data they generate is so large that satellite communication systems have severe limitations to download it, especially in SmallSats. It is therefore becoming urgent to develop efficient automated algorithms that can be executed in the limited capabilities of the onboard computers of these satellites, so as to reduce the amount of data to be stored and downloaded, while keeping as much information as possible for a given scene. In this work a band selection algorithm has been designed to deal with this problem. The proposed algorithm consists of the sequential selection of the spectral bands ranked using the amount of information provided by each band, and also the correlation of these bands with the previously selected ones. The algorithm performance is assessed by means of a suite of classification tests with hyperspectral datasets from different sensors. Results show comparable or even better performance than other existing Band Selection algorithms, while outperforming in terms of computational complexity, which makes it more suitable for SmallSats with limited computing resources.

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“…Therefore, the GNSS-R onboard processing algorithms should adapt to the new signals to take full advantage of the technique and thus improve the performances in different applications. Until now, many spaceborne GNSS-R constellations have been or will be launched which can process GNSS signals other than L1 C/A, such as Bufeng-1 [28] for L1/B1; Fengyun-3 [29] and Spire GNSS-R [30] for L1/E1/B1; FSSCat for E1 [31]; and HydroGNSS for L1/E1 and L5/E5A [32].…”

Section: Introductionmentioning

confidence: 99%

Coherent Combination of GPS III L1 C/A and L1C Signals for GNSS Reflectometry

Du,

Nan,

et al. 2024

IEEE Trans. Geosci. Remote Sensing

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With the evolution of Global Navigation Satellite System (GNSS), more GNSS satellites and civilian signals are available for GNSS Reflectometry (GNSS-R). Developments of new onboard processing strategies can improve the observation performance of spaceborne GNSS-R. To this end, this article proposes a new processing method by coherently combining reflected Global Positioning System (GPS) III L1 C/A and L1C signals. By exploiting the additional signal component, the signalto-noise ratio of the reflected signal can be significantly improved. Moreover, taking advantage of the narrower auto-correlation function of the combined signal, the spatial resolution and the performance on geophysical applications can be significantly improved. The proposed method has been validated by processing cyclone GNSS (CYGNSS) raw intermediate frequency data including the direct and reflected signals from GPS III satellites. The results indicate that the signal-to-noise ratio (SNR) of the combined reflected waveform can be improved by ∼2 dB compared to the L1 C/A waveform. Moreover, the SNR of the combined signal can be improved more efficiently using a longer coherent integration interval compared to the L1 C/A signal. Preliminary altimetric results demonstrate a 35.3%-61.6% improvement in the ranging standard deviation, and a 22.4%-64.4% improvement in the median absolute deviation, compared to L1 C/A measurements. Additionally, the correlation coefficient between combined measurements and wind speed improves by 26.3% on average compared to L1 C/A measurements, and 45.7% for high winds. This article presents a novel GNSS-R onboard signal processing method with improved performance, which can provide a reference for the design of future GNSS-R instruments.

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FSSCat: The Federated Satellite Systems ³Cat Mission: Demonstrating the capabilities of CubeSats to monitor essential climate variables of the water cycle [Instruments and Missions]

Cited by 16 publications

References 17 publications

Considerations for Eco-LeanSat Satellite Manufacturing and Recycling

Considerations for Eco-LeanSat Satellite Manufacturing and Recycling

Efficient Onboard Band Selection Algorithm for Hyperspectral Imagery in SmallSat Missions With Limited Downlink Capabilities

Coherent Combination of GPS III L1 C/A and L1C Signals for GNSS Reflectometry

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FSSCat: The Federated Satellite Systems 3Cat Mission: Demonstrating the capabilities of CubeSats to monitor essential climate variables of the water cycle [Instruments and Missions]

Cited by 16 publications

References 17 publications

Considerations for Eco-LeanSat Satellite Manufacturing and Recycling

Considerations for Eco-LeanSat Satellite Manufacturing and Recycling

Efficient Onboard Band Selection Algorithm for Hyperspectral Imagery in SmallSat Missions With Limited Downlink Capabilities

Coherent Combination of GPS III L1 C/A and L1C Signals for GNSS Reflectometry

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FSSCat: The Federated Satellite Systems ³Cat Mission: Demonstrating the capabilities of CubeSats to monitor essential climate variables of the water cycle [Instruments and Missions]