Advancing Commercial Space

Autonomous systems necessitates timely technological audits to evaluate their performance, conformance, and compliance. For the aviation industry, such a need has already been recognized by the Federal Aviation Administration (FAA) for the vehicles, sensors, and systems participating in Extensible Traffic Management (xTM) systems. xTM systems include the Unmanned Aircraft Systems (UAS) Traffic Management (UTM), Advanced Air Mobility (AAM), and Upper-Class E Traffic Management, and are complementary to the Air Traffic Management (ATM) system. xTM systems enable new entrants such as UAS and AAM vehicles to safely participate in the national airspace. To facilitate timely technological audits of the xTM participants, NASA Ames developed a novel technology that provides near-real-time verification and validation of autonomous flight operations of an individual vehicle or numerous diverse vehicles being managed by the xTM systems.

NASA's Armstrong Flight Research Center is offering companies that provide sensing solutions for monitoring of structures and asset management of storage tanks a unique opportunity to expand their product line to include unprecedented capabilities. Known as FOSS (for fiber optic sensing system), NASA's patented, award-winning technology portfolio combines advanced sensors and innovative algorithms into a robust package that accurately and cost-effectively monitors a host of critical parameters in real time. These include position/deformation (displacement, twist, rotation), stiffness (bending, torsion, vibration), operational loads (bending moments, shear loads, torques), strength/stress (pressure/fatigue, breakage prediction), and magnetic fields (cracks or other flaws in safety-critical metal structures) for structural health monitoring applications. In addition to monitoring the structure of a tank, FOSS is capable of sensing the tank's inventory, including amounts, temperatures, and stratification (oil vs. water, sediment vs. liquid, thermal layers).

Innovators at NASA's Armstrong Flight Research Center have found a way to incorporate wireless sensor technology in aerospace vehicles without adding the complexity and tonnage normally associated with physically modifying existing avionics. The solution: A single universal wireless access point or "gateway" that can communicate between existing onboard systems and any subscribed wireless device. This gateway can be easily reprogrammed to communicate with any wireless device, allowing engineers to add new sensing technology "at the speed of software." Furthermore, this gateway approach means that once a wireless sensor has been tested on a research vehicle or platform, it can be immediately integrated into other vehicles outfitted with the gateway. The gateway's architecture also holds promise for other industries seeking ways to capitalize on the advantages of wireless sensors.

At extreme temperatures, few electronic components are available to support intelligent data transfer over a common, linear combining medium such as wire or the airwaves. NASA Glenn's innovation allows the operating frequency of a sensor instrument to be time variant because the sensor is part of the frequency generator's transfer function. Each instrument associated with a sensor imparts a unique (orthogonal) signature onto the continuous output of that sensor. As a consequence, the outputs of numerous instruments may be simultaneously superimposed upon one another via a linear combining medium and then be separated at a common receiving node in a more temperate location using any number of linear source separation techniques. A listening node, using various techniques, can pick out the signal from a single sender, if it has unique qualities; e.g., a "voice." This technique is analogous to the human brain recognizing and following a single conversation in a party full of people talking and other distracting noises.

Innovators at NASA's Glenn Research Center have developed a technique using reversible non-linear amplitude compression to overcome hardware limitations of common high-speed data acquisition systems. The NASA Glenn technique measures electronic signals with high dynamic range, wide bandwidth, and high frequency. The technique implements a custom electronic circuit applied between the input of a data acquisition device, such as an oscilloscope, and a test article to be measured. The Glenn innovation also includes a software-based algorithm that is applied to the data acquired through the applied circuit and the data acquisition system.

SpaceCube is a cross-cutting, in-flight reconfigurable Field Programmable Gate Array (FPGA) based on-board hybrid science data processing system developed at the NASA Goddard Space Flight Center (GSFC). The goal of the SpaceCube program is to provide 10x to 100x improvements in on-board computing power while lowering relative power consumption and cost. The SpaceCube design strategy incorporates commercial radiation-tolerant Xilinx Virtex FPGA technology and couples it with an integrated upset detection and correction architecture to provide reliable order of magnitude improvements in computing power over traditional fully radiation-hardened flight systems.

SpaceCube 3.0 is a family of high-performance reconfigurable systems designed for spaceflight applications requiring on-board processing. SpaceCube 3.0 has greater processing performance over previous generations of SpaceCube. Many proposed missions require next generation on-board processing capabilities to meet specified mission goals. Advanced laser altimeter, radar, lidar, and hyper-spectral instruments are proposed for future missions, and all of these instrument systems require advanced onboard processing capabilities to facilitate data conversion. Besides an increased processing performance need, there is a need for a processor card capable of detecting and reacting to events, producing data products on-board, enabling sensor web multi-platform collaboration, performing on-board lossless data reduction by migrating typical ground-based processing functions on-board. In general, the processing needs of emerging space missions require a stronger flight processor card. SpaceCube 3.0 Flight Processor Card represents an improved flight processing system.

Currently there is no central database for space weather researchers and forecasters to ascertain observed space weather events. Instead, data is being recorded by scientists in a blog. However, this information is not easily searchable. This innovation is a database where weather events are entered and linkages, relationships, and cause-and-effects between various space weather events are recorded.

Accurate measurement and characterization of surface features on spherical objects, such as planets and moons, is a persistent challenge in planetary science, remote sensing, and atmospheric research. When viewed through traditional two-dimensional imaging, these spherical surfaces become distorted, particularly towards the edges, making it difficult to accurately measure important characteristics like area, perimeter, orientation, and spatial distribution. This distortion complicates the precise assessment of phenomena such as cloud coverage, geological features, or other surface events critical for scientific investigation. Thus, there is a need for a method that enables accurate and automated analysis without the distortion limitations inherent in traditional mapping approaches. NASA's innovative Grid-Oriented Normalization for Analysis of Spherical Areas (GONASA) directly addresses these challenges. The GONASA mathematical formula / algorithm provides a practical and accurate means of overcoming distortions through a novel, grid-based system of equal-area cells overlaid onto spherical surfaces. This enables users to reliably quantify and characterize objects on a sphere across entire surface, greatly enhancing the precision of scientific observations and improving the automation potential in processing and analyzing large volumes of data collected from satellite and spacecraft missions.

High-resolution heterodyne-based millimeter-wave spectrometers are used in remote sensing for studying planetary atmospheres. Currently, single-pixel receivers in the submillimeter-wave range provide incomplete information on molecular targets that require simultaneous measurement of differential tangential heights (e.g., molecules with variations in their distribution, pressure, and temperature-dependent spectral features). This increases the time needed to perform a scan using bulky and high power-consumption mechanisms in order to provide accurate atmospheric molecular measurements. Additionally, the narrow intermediate frequency (IF) bandwidth of current receiver technology limits the frequency window of molecular detection during the receiver down-conversation process. These limitations in receiver technology (e.g., bulky systems, high power consumption, limited IF bandwidth) hinder the the development of miniaturized spaceborne atmospheric remote sensing instruments that can be integrated and flown on small satellites. In response to this need, innovators at NASA’s Goddard Space Flight Center have developed a compact, sensitive, wideband and multi-pixel receiver to down-convert many molecular species simultaneously in the 530-600 GHz frequency range.

Innovators at NASA Johnson Space Center have developed and successfully flight tested a high-performance computing platform, known as the Descent and Landing Computer (DLC), to suit the demands of safe, autonomous, extraterrestrial spacecraft landings for robotic and human exploration missions. Unique to this platform is a datapath architecture that unencumbers microprocessors by isolating them from input and output interruptions, thus staving off latency and maximizing computational speed for the flight software. To safely land, the DLC must process landing-specific sensor data in real-time and relay this information to the primary flight computer for the spacecraft to avoid environmental hazards like craters and boulders. The datapath architecture presented allows for the DLC’s high-speed computational processing to provide this capability. This technology will be critical for safe access to other surface regions of the solar system in which spacecraft missions could not succeed with current landing capabilities. This datapath architecture technology is at a technology readiness level (TRL) 6 (system/subsystem prototype demonstration in a relevant environment) and is now available for your company to license. Please note that NASA does not manufacture products itself for commercial sale.

Determination of micrometeoroid/orbital debris (MMOD) impact on orbiting spacecraft currently requires visual inspection. For human-rated spacecraft such as the ISS and, previously, the Space Shuttle Orbiter, this has required crew time as well as vehicle assets to identify damage due to MMOD strikes. For unmanned spacecraft, there are no human assets present to conduct detailed surveys to ascertain potential damage. NASAs Langley Research Center has developed a strain-sensing system that can be affixed to a spacecrafts micrometeoroid/orbital debris (MMOD) shielding layer or structure. This technology detects the occurrence, time, location and severity of a MMOD strike on the shield, allowing for detection and location of potentially harmful MMOD strikes on both crewed and unmanned spacecraft. This knowledge is important because prolonged exposure to the on-orbit MMOD environment increases risk to vehicles in this environment including commercial crew vehicles expected to visit and remain for considerable periods of time at ISS.