High-Resolution Commercial Validation Products API

NASA's SpaceCube Mini SSDR is a 3.5”x3.5” card designed for use in CubeSats and SmallSats. The SSDR uses a radiation-tolerant field programmable gate array (FPGA) that interfaces with two independently controlled and powered banks of NAND Flash storage, providing up to 12 Terabits of storage capacity. The card includes multiple SpaceWire nodes and multi-gigabit transceivers for commanding and data transfer, various error prevention and correction mechanisms including Reed-Solomon encoding/decoding and data randomization schemes, and depacketizers/packetizers for handling data in CCSDS format. This NASA technology is innovative in its combination of high reliability for harsh radiation environments (e.g., geostationary orbit, lunar orbit and surface, etc.) with high-speed data transfer capabilities (400+ MB/s write, 600+ MB/s read) in a compact form factor. The design allows for selective population of NAND Flash modules and independent control of memory banks, enabling power optimization through features like single-bank operation. The card integrates with a modular architecture system in which multiple CubeSat-sized cards (e.g., processors, GPS, etc.) can be mixed and matched to meet specific mission requirements. The SSDR card includes radiation-hardened voltage regulators to ensure safe operation in space environments. The SSDR is ideal for small form factor satellites with some combination of the following requirements: (a) ability to store large amounts of data generated by high-performance detectors and sensors for extended durations (e.g., in environments without nearby relay capabilities), (b) ability to read and write data with high throughput, and (c) ability to operate in harsh radiation environments. It is fully compatible with NASA’s CubeSat Card Specification (CS2) and NASA’s SpaceCube v3.0 mini processing card, which is also available for licensing.

The Miniaturized Astrometric Alignment Sensor advances satellite capabilities for astrophysical measurements, necessary for formation flying, relative navigation, and virtual telescope capabilities. The sensor is a single assembly consisting of a small, low powered camera assembly. The sensor detects stellar objects from which both stellar and object tracking are performed. The sensor’s components consist of a low power camera assembly, interchangeable lenses, camera power supply, and image processing software and algorithms. The system functions by searching and identifying objects in the camera's field of view and tracking the objects against a selected star pattern with a central body of interest in the sensor's field of view. The Miniaturized Astrometric Alignment Sensor makes it possible to measure a spacecraft’s altitude and orientation with respect to known stellar objects. The instrument takes an image of a patch of sky, identifies the stars in that field of view, and compares the field view with a stored star map. The data is processed with a dedicated processor attached to the instrument to spell out the attitude and orientation of a spacecraft.

NASA Goddard Space Flight Center now offers a new capability for meeting this Big Data challenge: MERRA Analytic Services (MERRA/AS). MERRA/AS combines the power of high-performance computing, storage-side analytics, and web APIs to dramatically improve customer access to MERRA data. It represents NASAs first effort to provide Climate Analytics-as-a-Service. Retrospective analyses (or reanalyses) such as MERRA have long been important to scientists doing climate change research. MERRA is produced by NASAs Global Modeling and Assimilation Office (GMAO), which is a component of the Earth Sciences Division in Goddards Sciences and Exploration Directorate. GMAOs research and development activities aim to maximize the impact of satellite observations in climate, weather, atmospheric, and land prediction using global models and data assimilation. These products are becoming increasingly important to application areas beyond traditional climate science. MERRA/AS provides a new cloud-based approach to storing and accessing the MERRA dataset. By combining high-performance computing, MapReduce analytics, and NASAs Climate Data Services API (CDS API), MERRA/AS moves much of the work traditionally done on the client side to the server side, close to the data and close to large compute power. This reduces the need for large data transfers and provides a platform to support complex server-side data analysesit enables Climate Analytics-as-a-Service. MERRA/AS currently implements a set of commonly used operations (such as avg, min, and max) over all the MERRA variables. Of particular interest to many applications is a core collection of about two dozen MERRA land variables (such as humidity, precipitation, evaporation, and temperature). Using the RESTful services of the Climate Data Services API, it is now easy to extract basic historical climatology information about places and time spans of interest anywhere in the world. Since the CDS API is extensible, the community can participate in MERRA/ASs development by contributing new and more complex analytics to the MERRA/AS service. MERRA/AS demonstrates the power of CAaaS and advances NASAs ability to connect data, science, computational resources, and expertise to the many customers and applications it serves.

NASA Goddard Space Flight Center (GSFC) has developed a new approach that uses a single phased array antenna and a single pass configuration to generate interferograms, known as Digital Beamforming Interferometry. A digital beamforming radar system allows the implementation of non-conventional radar techniques, known as Digital Beamforming Synthetic Aperture Radar Multi-mode Operation (DBSAR). DBSAR is an L-Band airborne radar that combines advanced radar technology with the ability to implement multimode remote sensing techniques, including several variations of SAR, scatterometry over multiple beams, and an altimeter mode. The Multiple channel data acquired with a digital beamformer systems allows the synthesis of beams over separate areas of the antenna, effectively dividing the single antenna into two antennas. The InSAR technique is then achieved by generating interferograms from images collected with each of the antennas. Since the technique is performed on the data, it allows for synthesizing beams in different directions (or look angles) and performs interferometry over large areas. Digital Beamforming Interferometry has potential in many areas of radar applications. For example, NASA GSFC innovators developed the first P-Band Digital Beamforming Polarimetric Interferometric SAR Instrument to measure ecosystem structure, biomass, and surface water.

NASA Armstrong collaborated with the U.S. Air Force to develop algorithms that interpret highly encoded large area terrain maps with geographically user-defined error tolerances. A key feature of the software is its ability to locally decode and render DTMs in real time for a high-performance airplane that may need automatic course correction due to unexpected and dynamic events. Armstrong researchers are integrating the algorithms into a Global Elevation Data Adaptive Compression System (GEDACS) software package, which will enable customized maps from a variety of data sources. How It Works The DTM software achieves its high performance encoding and decoding processes using a unique combination of regular and semi-regular geometric tiling for optimal rendering of a requested map. This tiling allows the software to retain important slope information and continuously and accurately represent the terrain. Maps and decoding logic are integrated into an aircraft's existing onboard computing environment and can operate on a mobile device, an EFB, or flight control and avionics computer systems. Users can adjust the DTM encoding routines and error tolerances to suit evolving platform and mission requirements. Maps can be tailored to flight profiles of a wide range of aircraft, including fighter jets, UAVs, and general aviation aircraft. The DTM and GEDACS software enable the encoding of global digital terrain data into a file size small enough to fit onto a tablet or other handheld/mobile device for next-generation ground collision avoidance. With improved digital terrain data, aircraft could attain better performance. The system monitors the ground approach and an aircraft's ability to maneuver by predicting several multidirectional escape trajectories, a feature that will be particularly advantageous to general aviation aircraft. Why It Is Better Conventional DTM encoding techniques used aboard high-performance aircraft typically achieve relatively low encoding process ratios. Also, the computational complexity of the decoding process can be high, making them unsuitable for the real-time constrained computing environments of high-performance aircraft. Implementation costs are also often prohibitive for general aviation aircraft. This software achieves its high encoding process ratio by intelligently interpreting its maps rather than requiring absolute retention of all data. For example, the DTM software notes the perimeter and depth of a mining pit but ignores contours that are irrelevant based on the climb and turn performance of a particular aircraft and therefore does not waste valuable computational resources. Through this type of intelligent processing, the software eliminates the need to maintain absolute retention of all data and achieves a much higher encoding process ratio than conventional terrain-mapping software. The resulting exceptional encoding process allows users to store a larger library of DTMs in one place, enabling comprehensive map coverage at all times. Additionally, the ability to selectively tailor resolution enables high-fidelity sections of terrain data to be incorporated seamlessly into a map.