The Little Photometer That Could: Technical Challenges and Science Results from the Kepler Mission

The Kepler spacecraft launched on March 7, 2009, initiating NASA's first search for Earth-size planets orbiting Sun-like stars. Since launch, Kepler has announced the discovery of 17 exoplanets, including a system of six transiting a Sun-like star, Kepler-11, and the first confirmed rocky planet, Kepler-10b, with a radius of 1.4 that of Earth. Kepler is proving to be a cornucopia of discoveries: it has identified over 1200 candidate planets based on the first 120 days of observations, including 54 that are in or near the habitable zone of their stars, and 68 that are 1.2 Earth radii or smaller. An astounding 408 of these planetary candidates are found in 170 multiple systems, demonstrating the compactness and flatness of planetary systems composed of small planets. Never before has there been a photometer capable of reaching a precision near 20 ppm in 6.5 hours and capable of conducting nearly continuous and uninterrupted observations for months to years. In addition to exoplanets, Kepler is providing a wealth of astrophysics, and is revolutionizing the field of asteroseismology. Designing and building the Kepler photometer and the software systems that process and analyze the resulting data to make the discoveries presented a daunting set of challenges, including how to manage the large data volume. The challenges continue into flight operations, as the photometer is sensitive to its thermal environment, complicating the task of detecting 84 ppm drops in brightness corresponding to Earth-size planets transiting Sun-like stars

GPU accelerated multispectral EO imagery optimised CCSDS-123 lossless compression implementation

Continual advancements in Earth Observation (EO) optical imager payloads has led to a significant increase in the volume of multispectral data generated onboard EO satellites. As a result, a growing onboard data bottleneck need to be alleviated. One technique commonly used is onboard image compression. However, the performance of traditional space qualified processors, such as radiation hardened FPGAs, are not able to meet current nor future onboard data processing requirements. Therefore, a new high capability hardware architecture is required. In previous work a new GPU accelerated scalable heterogeneous hardware architecture for onboard data processing was proposed. In this paper, two new CUDA GPU implementations of the state-of-the-art lossless multidimensional image compression algorithm CCSDS-123, are discussed. The first implementation is a generic CUDA implementation of the CCSDS-123 algorithm whilst the second is optimised specifically for multispectral EO imagery. Both implementations utilise image tiling to leverage an additional axis for algorithm parallelisation to increase processing throughput. The CUDA implementation and optimisation techniques deployed are discussed in the paper. In addition, compression ratio and throughput performance results are presented for each implementation. Further experimental studies into the relationships between algorithm user definable compression parameters, tile sizes, tile dimensions and the achieved compression ratio and throughput, were performed

The Space and Earth Science Data Compression Workshop

This document is the proceedings from a Space and Earth Science Data Compression Workshop, which was held on March 27, 1992, at the Snowbird Conference Center in Snowbird, Utah. This workshop was held in conjunction with the 1992 Data Compression Conference (DCC '92), which was held at the same location, March 24-26, 1992. The workshop explored opportunities for data compression to enhance the collection and analysis of space and Earth science data. The workshop consisted of eleven papers presented in four sessions. These papers describe research that is integrated into, or has the potential of being integrated into, a particular space and/or Earth science data information system. Presenters were encouraged to take into account the scientists's data requirements, and the constraints imposed by the data collection, transmission, distribution, and archival system

Protocols for Store-and-Forward Message Switching via Microsatellites

The authors have developed a suite of protocols specifically optimized for use on store-and-forward microsatellite communications missions. The protocols support networks in which user terminals directly access the store-and-forward satellite to transfer electronic mail. The authors\u27 PACSAT Protocol Suite includes a message format standard, a virtual-circuit directory and file transfer service, and a datagram based point-to-multipoint broadcast protocol. An implementation of this suite has been operating on the UoSAT-3 PACSAT Communications Experiment (PCE) for twelve months and on the AMSAT Microsats for seven months. During this period, hundreds of small and medium-sized ground terminals in all parts of the world have accessed the satellites. On-board software monitors network activity closely, and usage statistics for UoSAT-3 are gathered regularly at the UoSAT Command Station. Based on this data and the reported experiences of regular system users, we compare the effectiveness of the various protocols. From these comparisons we make some recommendations which are generally applicable to store-and-forward microsatellite missions. This paper describes the design of the PACSAT Protocol Suite and the UoSAT-3 and Microsat implementations. It summarizes the in-orbit performance results, and concludes with recommendations for future store-and-forward microsatellite missions

An Analysis of Storage Virtualization

Investigating technologies and writing expansive documentation on their capabilities is like hitting a moving target. Technology is evolving, growing, and expanding what it can do each and every day. This makes it very difficult when trying to snap a line and investigate competing technologies. Storage virtualization is one of those moving targets. Large corporations develop software and hardware solutions that try to one up the competition by releasing firmware and patch updates to include their latest developments. Some of their latest innovations include differing RAID levels, virtualized storage, data compression, data deduplication, file deduplication, thin provisioning, new file system types, tiered storage, solid state disk, and software updates to coincide these technologies with their applicable hardware. Even data center environmental considerations like reusable energies, data center environmental characteristics, and geographic locations are being used by companies both small and large to reduce operating costs and limit environmental impacts. Companies are even moving to an entire cloud based setup to limit their environmental impact as it could be cost prohibited to maintain your own corporate infrastructure. The trifecta of integrating smart storage architectures to include storage virtualization technologies, reducing footprint to promote energy savings, and migrating to cloud based services will ensure a long-term sustainable storage subsystem

Remote Sensing Data Compression

A huge amount of data is acquired nowadays by different remote sensing systems installed on satellites, aircrafts, and UAV. The acquired data then have to be transferred to image processing centres, stored and/or delivered to customers. In restricted scenarios, data compression is strongly desired or necessary. A wide diversity of coding methods can be used, depending on the requirements and their priority. In addition, the types and properties of images differ a lot, thus, practical implementation aspects have to be taken into account. The Special Issue paper collection taken as basis of this book touches on all of the aforementioned items to some degree, giving the reader an opportunity to learn about recent developments and research directions in the field of image compression. In particular, lossless and near-lossless compression of multi- and hyperspectral images still remains current, since such images constitute data arrays that are of extremely large size with rich information that can be retrieved from them for various applications. Another important aspect is the impact of lossless compression on image classification and segmentation, where a reasonable compromise between the characteristics of compression and the final tasks of data processing has to be achieved. The problems of data transition from UAV-based acquisition platforms, as well as the use of FPGA and neural networks, have become very important. Finally, attempts to apply compressive sensing approaches in remote sensing image processing with positive outcomes are observed. We hope that readers will find our book useful and interestin

The Difficult Road to Mars: A Brief History of Mars Exploration in the Soviet Union

Perminov was the leading designer for Mars and Venus spacecraft at the Soviet Lavochkin design bureau in the early days of Martian exploration. In addition to competing with the U.S. to get to the Moon, the Soviets also struggled to beat the U.S. to Mars during the Cold War. Throughout the 1960s and 1970s, the Soviets attempted to send a number of robotic probes to Mars, but for a variety of reasons, most of these missions ended in failure. Despite these overall failures, the Soviets garnered a great deal of scientific and technical knowledge through these efforts. This monograph tells some fascinating, but little-known, stories

Application of nanosatellites for lunar missions

Two major themes for the space sector in recent years have been the resurgence of missions to the Moon, facilitating the expansion of human presence into the Solar System, and the rapid growth in CubeSat launches. Lunar missions will play an important role in sustainable space exploration, as discussed in the Global Exploration Roadmap. The Roadmap outlines the next steps for the current and next generation of explorers and reaffirms the interest of 14 space agencies to return to the Moon. Over the past decade, a more daring approach to space innovation and the proliferation of low-cost small satellites have invited commercialization and, subsequently, have accelerated the development of miniaturized technologies and substantially reduced the costs associated with CubeSats. In this context, CubeSats are increasingly being considered as platforms for pioneering missions beyond low-Earth orbit. This paper describes a 3U nanosatellite mission to the Moon, designed as part of the UKSEDS Satellite Design Competition, capable of capturing and analysing details of the lunar environment. To achieve the primary mission objectives, a camera and an infrared spectrometer have been included to relay information about historic lunar landmarks to Earth. The design was developed to be integrated with Open Cosmos' OpenKit and reviewed by experts in the field from SSPI. The paper includes a detailed assessment of the current state of miniaturized instruments and the quality of scientific return which can be achieved by a lunar CubeSat mission. This concludes in an overall feasibility study of lunar CubeSats, a discussion of the current limitations and challenges associated with CubeSat technologies and a framework for future missions

Cyber-Human Systems, Space Technologies, and Threats

CYBER-HUMAN SYSTEMS, SPACE TECHNOLOGIES, AND THREATS is our eighth textbook in a series covering the world of UASs / CUAS/ UUVs / SPACE. Other textbooks in our series are Space Systems Emerging Technologies and Operations; Drone Delivery of CBNRECy – DEW Weapons: Emerging Threats of Mini-Weapons of Mass Destruction and Disruption (WMDD); Disruptive Technologies with applications in Airline, Marine, Defense Industries; Unmanned Vehicle Systems & Operations On Air, Sea, Land; Counter Unmanned Aircraft Systems Technologies and Operations; Unmanned Aircraft Systems in the Cyber Domain: Protecting USA’s Advanced Air Assets, 2nd edition; and Unmanned Aircraft Systems (UAS) in the Cyber Domain Protecting USA’s Advanced Air Assets, 1st edition. Our previous seven titles have received considerable global recognition in the field. (Nichols & Carter, 2022) (Nichols, et al., 2021) (Nichols R. K., et al., 2020) (Nichols R. , et al., 2020) (Nichols R. , et al., 2019) (Nichols R. K., 2018) (Nichols R. K., et al., 2022)https://newprairiepress.org/ebooks/1052/thumbnail.jp