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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

On The Processing of Log Files for Monitoring Antenna Health

In order to improve the quality of geodetic results, we have developed an infrastructure for timely processing of telemetry from IVS observing stations. We check every hour for new log files with telemetry from both VLBI observing sessions, single dish experiments, and stow-in data collection and automatically process them. The telemetry data we use is the system temperature, phase calibration phases and amplitudes, system equivalent flux density, and the differences between formatter clock and GPS clock. For the system temperature and phase calibration, processing includes filtering out outliers and computing averages and rms of the scatter in each scan. Furthermore, for the phase calibration we also compute the group delay and detect spurious signals. Cleaned and post-processed telemetry is archived. Our process detects abnormalities, such as, anomalously high system temperature, unstable phase calibration phases, jumps in the GPS and formatter clock differences, and others. With our procedure, the latency of detection of station abnormalities is reduced to less than two hours. Early detection of abnormalities reduces the amount of affected data since station personnel get early alerts. We discuss our experience of running this system since 2022.

VLBI↗
NASA NTRSDate not supplied

On The Processing of Log Files for Monitoring Antenna Health

In order to improve the quality of geodetic results, we have developed an infrastructure for timely processing of telemetry from IVS observing stations. We check every hour for new log files with telemetry from both VLBI observing sessions, single dish experiments, and stow-in data collection and automatically process them. The telemetry data we use is the system temperature, phase calibration phases and amplitudes, system equivalent flux density, and the differences between formatter clock and GPS clock. For the system temperature and phase calibration, processing includes filtering out outliers and computing averages and rms of the scatter in each scan. Furthermore, for the phase calibration we also compute the group delay and detect spurious signals. Cleaned and post-processed telemetry is archived. Our process detects abnormalities, such as, anomalously high system temperature, unstable phase calibration phases, jumps in the GPS and formatter clock differences, and others. With our procedure, the latency of detection of station abnormalities is reduced to less than two hours. Early detection of abnormalities reduces the amount of affected data since station personnel get early alerts. We discuss our experience of running this system since 2022.

Phase Calibration↗
NASA NTRS2008

Orchestrator Telemetry Processing Pipeline

Orchestrator is a software application infrastructure for telemetry monitoring, logging, processing, and distribution. The architecture has been applied to support operations of a variety of planetary rovers. Built in Java with the Eclipse Rich Client Platform, Orchestrator can run on most commonly used operating systems. The pipeline supports configurable parallel processing that can significantly reduce the time needed to process a large volume of data products. Processors in the pipeline implement a simple Java interface and declare their required input from upstream processors. Orchestrator is programmatically constructed by specifying a list of Java processor classes that are initiated at runtime to form the pipeline. Input dependencies are checked at runtime. Fault tolerance can be configured to attempt continuation of processing in the event of an error or failed input dependency if possible, or to abort further processing when an error is detected. This innovation also provides support for Java Message Service broadcasts of telemetry objects to clients and provides a file system and relational database logging of telemetry. Orchestrator supports remote monitoring and control of the pipeline using browser-based JMX controls and provides several integration paths for pre-compiled legacy data processors. At the time of this reporting, the Orchestrator architecture has been used by four NASA customers to build telemetry pipelines to support field operations. Example applications include high-volume stereo image capture and processing, simultaneous data monitoring and logging from multiple vehicles. Example telemetry processors used in field test operations support include vehicle position, attitude, articulation, GPS location, power, and stereo images.

Powell, Mark↗
NASA NTRS1998

X-33 Integrated Test facility, Extended Range Simulation

In support of the X-33 Single Stage To Orbit program, NASA Dryden Flight Research Center was selected to provide continuous communications coverage of the X-33 vehicle from launch, through landing at Malmstrom Air Force Base, Montana and Michaels Army Air Field, Utah. An extensive real-time range simulation capability is being developed to ensure successful communications with the autonomous X-33 vehicle. This paper will provide an overview of the various levels of simulation being developed to support the X-33 extended range subsystems. These subsystems include the Flight Termination System, L-Band command uplink subsystem and the S-Band telemetry downlink subsystem. In addition, the radar model developed provides continuous azimuth, elevation and range information based on the flight trajectory. The Dynamic Ground Station Analysis model developed by NASA Goddard Space Flight Center, calculate the received signal strength at each ground station. This model takes into consideration Radio Frequency (RF) link parameters such as frequency, antenna gain, space loss, plasma effects and the vehicle's position and attitude at any point in time during the flight path. All three RF links are then attenuated based on this calculated level and the RF signals are sent into telemetry receivers to emulate remote sites, or the power incident on the vehicle from uplinked signals. The best source received telemetry data is then passed back to the Launch and Mission Control Monitoring System (LMCMS) resident in the Operations Control Center. The LMCMS also provides the range simulation system the uplink command combined with differential GPS corrections. Later stages will require the progressive integration of actual range hardware with this simulation effort, leading to communication between telemetry, uplink and FTS antennas at NASA Dryden Flight Research Center, with vehicle antennas mounted on the Walter C. Williams Research Aircraft Integration Facility (RAIF). Decommutated Pulse Code Modulated (PCM) data is displayed on one of the four monitors that comprise the Range Safety Officer's (RSO) station. Also displayed are instantaneous impact prediction models, and Federal Aviation Administration (FAA) data for notification of other traffic in the area. Aside from initiating the flight termination command and validating communication links, the RSO station with the range simulation will be used to provide both range control and range safety officers training. The training is necessary to perform their respective functions with greater levels of confidence prior to first flight.

Sharma, Ashley↗
NASA NTRS2008

GPS Metric Tracking Unit

As Global Positioning Satellite (GPS) applications become more prevalent for land- and air-based vehicles, GPS applications for space vehicles will also increase. The Applied Technology Directorate of Kennedy Space Center (KSC) has developed a lightweight, low-cost GPS Metric Tracking Unit (GMTU), the first of two steps in developing a lightweight, low-cost Space-Based Tracking and Command Subsystem (STACS) designed to meet Range Safety's link margin and latency requirements for vehicle command and telemetry data. The goals of STACS are to improve Range Safety operations and expand tracking capabilities for space vehicles. STACS will track the vehicle, receive commands, and send telemetry data through the space-based asset, which will dramatically reduce dependence on ground-based assets. The other step was the Low-Cost Tracking and Data Relay Satellite System (TDRSS) Transceiver (LCT2), developed by the Wallops Flight Facility (WFF), which allows the vehicle to communicate with a geosynchronous relay satellite. Although the GMTU and LCT2 were independently implemented and tested, the design collaboration of KSC and WFF engineers allowed GMTU and LCT2 to be integrated into one enclosure, leading to the final STACS. In operation, GMTU needs only a radio frequency (RF) input from a GPS antenna and outputs position and velocity data to the vehicle through a serial or pulse code modulation (PCM) interface. GMTU includes one commercial GPS receiver board and a custom board, the Command and Telemetry Processor (CTP) developed by KSC. The CTP design is based on a field-programmable gate array (FPGA) with embedded processors to support GPS functions.

Source record↗
DOE OSTI2021

High-dimensional Data-driven Energy optimization for Multi-Modal Transit Agencies (HD-EMMA) (Final Technical Report)

Public bus transit services in the U.S. are responsible for at least 19.7 million metric tons of CO 2 emission annually. Electric vehicles (EVs) can have a much lower environmental impact than comparable internal combustion engine vehicles (ICEVs), especially in urban areas. Unfortunately, EVs are also much more expensive than ICEVs. As a result, many public transit agencies can afford only mixed fleets of transit vehicles, consisting of EVs, hybrids (HEVs), and ICEVs. Transit agencies that operate such mixed fleets of vehicles face a challenging optimization problem: these agencies need to decide which vehicles are assigned to serving which transit trips. Since the advantage of EVs over ICEVs varies depending on the route and time of day (e.g., the benefit of EVs is higher in slower traffic with frequent stops and lower on highways), the assignment can have a significant effect on energy use and, hence, environmental impact. Through this project, we have developed reference data about energy collections and constructed a set of machine learning models that can accurately predict the energy consumption for the whole fleet at the level of each trip. We have used these models to develop a scheduling and assignment strategy that can rotate the different vehicle types across the transit agencies’ routes. The optimization algorithm ensures that the vehicles are matched to trips considering weather patterns, expected congestion, and road gradients to minimize the overall energy usage. We list the key observations from our project for other practitioners below. Details are available in the report, and the list of source code and our publications are included in the appendix. 1. We have demonstrated the feasibility of collecting, merging and analyzing large volumes of high-resolution real-world telemetry data from a mixed vehicle fleet. To mitigate the inherent noise of the recorded GPS points, the team developed an algorithm that filters data and maps the points onto a street. The algorithm considers previous and subsequent location measurements and different characteristics of nearby streets to determine how likely the vehicle travels on them. Then, the team segmented the time series into disjoint contiguous samples based on adjacent road segments and repeated the outlier detection and removal. For each data point, the team added features corresponding to elevation changes within the samples, weather features, such as temperature, and traffic data, such as speed ratio between actual speed and free-flow speed. 2. We have developed two forms of machine learning models that be used to understand and analyze the energy operations of a mixed vehicle transit fleet. The micro prediction model provides estimates of instantaneous energy prediction for all types of buses (diesel, hybrid, and electric). Such a model is important in evaluating the energy impacts of real-time bus operation strategies, but it is challenging due to diversified driving cycles of transit buses. The model can help the drivers understand the impact of their driving behaviors and short-term congestions. The macro prediction models estimate average energy consumption across the whole trip considering the features: distance traveled, various road-type features, elevation change, day of the week, time of day, various weather features (temperature, humidity, etc.), and traffic features (speed ratio and jam factor). 3. We have demonstrated that it is possible to transfer the machine learning models we have developed in this project to other teams and cities by using inductive transfer learning. We also showed that the performance of the macro energy prediction models can be improved using a multi-task learning approach where the learning parameters are shared between the models being developed for different vehicle types. The advantage of this approach is improved learning performance as the models can exploit common spatio-temporal and environmental characteristics. 4. Finally, we have developed trip and vehicle assignment and scheduling algorithms that use the energy prediction models and develop a trip to vehicle type (diesel, electric, hybrid) assignment for the whole operation to reduce overall emissions and cost. We have shown through simulations that the proposed algorithms can save $\$$ 48,910 in energy costs and 175 metric tons of CO 2 emission annually for CARTA.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2004

Space-Based Telemetry And Range Safety Flight Demonstration #1

The basic ability of STARS to maintain a satellite communications link with TDRSS satellites during dynamic aircraft flights was successfully demonstrated during FD 1. The Range Safety and Range User systems' link margins were measured. The ability to acquire/reacquire and maintain lock between a high-dynamic vehicle and a satellite-based system was demonstrated. The Range Safety system simultaneously received and processed command links from space and ground transmitters and provided near real-time Range Safety telemetry to DFRC, which then sent it in near real time to KSC, GSFC, and WFF for monitoring. The GPS receiver maintained track except during extremely dynamic maneuvers. The Range User system sent data at three different data rates. There were excellent cooperation and support from the different Centers, contractors, and Ranges. A large amount of data was recorded and extensive post-flight analysis was performed. The Range User TDRSS link margin met or exceeded the predicted performance at three different data rates. The Range Safety launch-head link margins generally agreed with the predicted performance. The UPS positions and velocities agreed with those from tracking radar to within about 20 m and a few rn/s. The link margins for the Range Safety TDRSS telemetry link were less than expected. The link margin for one TDRSS command link LPT channel was occasionally much less than the other. Additional post-flight testing has yet to identify the root causes of these results. There were many lessons learned from this first set of test flights. The most important one is that more time and testing are needed for each step to deal with the inevitable problems. It is vital that these lessons be among the primary areas of study that will carry over from FD#1 to FD#2, which is currently scheduled for early FY05 at DFRC and will use a specially designed Ku-band phased array antenna for the Range User system. The next series of flight demonstrations scheduled for late 2004 at DFRC will incorporate many lessons learned from FD#1. A specially designed Ku-band phased array antenna will be used with the Range User system. A test flight on a hypersonic vehicle is planned by the end of 2006.

Demspm. Erol↗
NASA NTRS2001

A Space Based Internet Protocol System for Launch Vehicle Tracking and Control

Personnel from the Goddard Space Flight Center Wallops Flight Facility (GSFC/WFF) in Virginia are responsible for the overall management of the NASA Sounding Rocket and Scientific Balloon Programs. Payloads are generally in support of NASA's Space Science Enterprise's missions and return a variety of scientific data as well as providing a reasonably economical means of conducting engineering tests for instruments and devices used on satellites and other spacecraft. Sounding rockets used by NASA can carry payloads of various weights to altitudes from 50 km to more than 1,300 km. Scientific balloons can carry a payload weighing as much as 3,630 Kg to an altitude of 42 km. Launch activities for both are conducted not only from established ranges, but also from remote locations worldwide requiring mobile tracking and command equipment to be transported and set up at considerable expense. The advent of low earth orbit (LEO) commercial communications satellites provides an opportunity to dramatically reduce tracking and control costs of these launch vehicles and Unpiloted Aerial Vehicles (UAVs) by reducing or eliminating this ground infrastructure. Additionally, since data transmission is by packetized Internet Protocol (IP), data can be received and commands initiated from practically any location. A low cost Commercial Off The Shelf (COTS) system is currently under development for sounding rockets that also has application to UAVs and scientific balloons. Due to relatively low data rate (9600 baud) currently available, the system will first be used to provide GPS data for tracking and vehicle recovery. Range safety requirements for launch vehicles usually stipulate at least two independent tracking sources. Most sounding rockets flown by NASA now carry GP~ receivers that output position data via the payload telemetry system to the ground station. The Flight Modem can be configured as a completely separate link thereby eliminating the requirement for tracking radar. The system architecture that integrates antennas, GPS receiver, commercial satellite packet data modem, and a single board computer with custom software is described along with the technical challenges and the plan for their resolution. These include antenna development, high Doppler rates, reliability, environmental ruggedness, hand over between satellites, and data security. An aggressive test plan is included which, in addition to environmental testing, measures bit error rate, latency and antenna patterns. Actual launches on a sounding rocket and various aircraft flights have taken place. Flight tests are planned for the near future on aircraft, long duration balloons and sounding rockets. These results, as well as the current status of the project, are reported.

Bull, Barton↗
NASA NTRS2018

Using GPS Receivers 1PPS Output to Verify Time Stamp Accuracy and Measure Propagation Delay

A simple Pulse Overlay (PO) circuit using a logic OR gate was developed to overlay a precise leading edge 1 Pulse Per Second (1PPS) time reference marker from a GPS receiver onto a Non-Return -to- Zero-Level (NRZ-L) Pulse Code Modulation (PCM) telemetry data stream to validate time stamp accuracy and measure propagation delay (PD) in telemetry equipment.

telemetry↗
NASA NTRS1999

Ground-Based GPS as a Calibration/Validation Tool for Tropospheric Sensing Instruments

The tropospheric sensing capabilities of ground-based GPS have been the subject of intensive validation efforts in recent years. But a maturing GPS technology is now rapidly becoming a valuable calibration/validation tool in its own right. We will describe two applications where ground-based GPS receivers have been used as a calibration/validation tool. The first such case is the Cassini gravitational wave media calibration project. A water vapor radiometer (WVR) will calibrate the telemetry signal from the Cassini spacecraft for line-of-sight wet tropospheric fluctuations. The demanding mission specifications require that the WVR's retrieval of wet delay from measurements of brightness temperature be precisely calibrated. We will describe the results from a special campaign to calibrate the WVR's retrieval algorithm with GPS. The second case involves the Topex/Poseidon microwave radiometer (TMR) which is used to calibrate the altimetric measurement for the effect of tropospheric water vapor. Using GPS data from 1992 to 1997 we detected an anomalous drift in columnar water vapor measurements from the TMR. The TMR's spurious drift implies that the uncalibrated estimate of global mean sea level change from Topex/Poseidon is too low by approximately 1 mm/yr. We will discuss the challenges of using long-term time series and problems relating to using the global GPS network as a calibration tool.

Bar-Sever, Y. E.↗
NASA NTRS2012

High-Altitude MMIC Sounding Radiometer for the Global Hawk Unmanned Aerial Vehicle

Microwave imaging radiometers operating in the 50-183 GHz range for retrieving atmospheric temperature and water vapor profiles from airborne platforms have been limited in the spatial scales of atmospheric structures that are resolved not because of antenna aperture size, but because of high receiver noise masking the small variations that occur on small spatial scales. Atmospheric variability on short spatial and temporal scales (second/ km scale) is completely unresolved by existing microwave profilers. The solution was to integrate JPL-designed, high-frequency, low-noise-amplifier (LNA) technology into the High-Altitude MMIC Sounding Radiometer (HAMSR), which is an airborne microwave sounding radiometer, to lower the system noise by an order of magnitude to enable the instrument to resolve atmospheric variability on small spatial and temporal scales. HAMSR has eight sounding channels near the 60-GHz oxygen line complex, ten channels near the 118.75-GHz oxygen line, and seven channels near the 183.31-GHz water vapor line. The HAMSR receiver system consists of three heterodyne spectrometers covering the three bands. The antenna system consists of two back-to-back reflectors that rotate together at a programmable scan rate via a stepper motor. A single full rotation includes the swath below the aircraft followed by observations of ambient (roughly 0 C in flight) and heated (70 C) blackbody calibration targets located at the top of the rotation. A field-programmable gate array (FPGA) is used to read the digitized radiometer counts and receive the reflector position from the scan motor encoder, which are then sent to a microprocessor and packed into data files. The microprocessor additionally reads telemetry data from 40 onboard housekeeping channels (containing instrument temperatures), and receives packets from an onboard navigation unit, which provides GPS time and position as well as independent attitude information (e.g., heading, roll, pitch, and yaw). The raw data files are accessed through an Ethernet port. The HAMSR data rate is relatively low at 75 kbps, allowing for real-time access over the Global Hawk high-data-rate downlink. Once on the ground, the raw data are unpacked and processed through two levels of processing. The Level 1 product contains geo-located, time-stamped, calibrated brightness temperatures for the Earth scan. These data are then input to a lD variational retrieval algorithm to produce temperature, water vapor, and cloud liquid water profiles, as well as several derived products such as potential temperature and relative humidity.

Brown, Shannon T.↗
DOE OSTI2022

Bayesian State-Space Modeling Framework for Understanding and Predicting Golden Eagle Movements Using Telemetry Data

Predicting raptor movements through a wind power plant under given atmospheric and topographical conditions is a crucial first step in the overall goal of quantifying the risk of turbine-related collisions and mortalities. Extracting behavioral traits of golden eagles (Aquila chrysaetos) from telemetry data requires the fusion of noisy and sparse movement data (location, heading, velocity) with a stochastic mathematical representation of the eagles' decision-making processes. In this study, we framed this problem in a Bayesian state-space framework where both observations and decision-making are assumed to be stochastic processes connected through hidden states (mode of flight, intent), and the unknown model parameters are assumed to be random variables that are calibrated using the available telemetry data. This framework allowed for rigorous consideration of underlying uncertainties while allowing for both data and prior biological knowledge to contribute to a probabilistic and predictive agent-based movement model. We implemented and applied the Bayesian framework to understand movement behavior of 23 GPS-tagged golden eagles travelling in the western US for years 2019 and 2020. Our preliminary findings show that the Bayesian state-space framework provides a robust inverse modeling apparatus to decode eagle behavioral characteristics from telemetry data. This study was primarily aimed at verifying and validating the framework with selected golden eagle tracks (both long- and short-ranged), with future research aimed at extending the framework to include multi-mode flight, consideration of atmospheric data and uplift mechanisms, eagle-to-eagle interaction, and eagle-to-turbine interaction.

Bayesian modeling↗
NASA NTRS2003

MiniAERCam Ranging

Johnson Space Center (JSC) is designing a small, remotely controlled vehicle that will carry two color and one black and white video cameras in space. The device will launch and retrieve from the Space Vehicle and be used for remote viewing. Off the shelf cellular technology is being used as the basis for communication system design. Existing plans include using multiple antennas to make simultaneous estimates of the azimuth of the MiniAERCam from several sites on the Space Station and use triangulation to find the location of the device. Adding range detection capability to each of the nodes on the Space Vehicle would allow an estimate of the location of the MiniAERCam to be made at each Communication And Telemetry Box (CATBox) independent of all the other communication nodes. This project will investigate the techniques used by the Global Positioning System (GPS) to achieve accurate positioning information and adapt those strategies that are appropriate to the design of the CATBox range determination system.

Talley, Tom↗
NASA NTRS1977

Interpolation schemes for orbit determination with the global positioning system

This paper demonstrates that the Global Positioning System (GPS) and simple interpolation schemes can be utilized to satisfy typical orbit determination demands of applications satellites. The complete GPS consists of 24 satellites and permits a position fix of a user satellite at any arbitrary instant. The interpolation formulae used in this report fit generalized Keplerian orbits through a number of position fixes. For a given accuracy level the telemetry requirements as measured by the time intervals between position fixes and the computational load of an interpolation as measured by the number of points through which a generalized Keplerian orbit is fitted vary inversely. A set of possible compromises between these two factors is presented. The Phase I GPS consists of 6 satellites and permits a position fix of a user satellite just 36% of the time. It is shown that with this system more sophisticated interpolation schemes which model atmospheric drag and higher degree terms of the earth's gravity field must be employed to obtain accurate orbits.

Argentiero, P.↗
NASA NTRS1980

ESTL RF communication simulators for orbiter payloads and GPS satellites

The simulator contains a transponder compatible with the NASA Spaceflight Tracking and Data Network, a transponder compatible with the DOD Space Ground Link System, and associated command detector units and telemetry multiplexer/modulators. It is pointed out that during selected ESTL tests, the actual payload transponder will be configured with the Payload Communications Simulator (PCS) telemetry multiplexer and modulators to form a complete payload communication system. A block diagram of the PCS is included.

Schmidt, O. L.↗
NASA NTRS1996

Cesium and Rubidium Frequency Standards Status and Performance on the GPS Program

This paper is an update of the on-orbit operational performance of the frequency standards on the last Block 1 Navstar satellite (GPS-10), the complete Block 2 Navstar satellites (GPS-13 to 21) and the Block 2A Navstar (GPS-22 to 40) satellites. Since the status of the GPS constellation is now at full operational capability (FOC), a minimum of twenty-four satellites are in position with all the necessary tests successfully completed. The evolution of frequency standards on board the GPS vehicles will be presented with corresponding results. Various methods and techniques will be presented to show on-orbit life time, down time, state of health telemetry, on-orbit trending and characterization of all the frequency standards. Other topics such as reliability, stability, clock quirks and idiosyncrasies of each vehicle will be covered.

VanMelle, M. J.↗
NASA NTRS2010

A GPS-Based Pitot-Static Calibration Method Using Global Output-Error Optimization

Pressure-based airspeed and altitude measurements for aircraft typically require calibration of the installed system to account for pressure sensing errors such as those due to local flow field effects. In some cases, calibration is used to meet requirements such as those specified in Federal Aviation Regulation Part 25. Several methods are used for in-flight pitot-static calibration including tower fly-by, pacer aircraft, and trailing cone methods. In the 1990 s, the introduction of satellite-based positioning systems to the civilian market enabled new inflight calibration methods based on accurate ground speed measurements provided by Global Positioning Systems (GPS). Use of GPS for airspeed calibration has many advantages such as accuracy, ease of portability (e.g. hand-held) and the flexibility of operating in airspace without the limitations of test range boundaries or ground telemetry support. The current research was motivated by the need for a rapid and statistically accurate method for in-flight calibration of pitot-static systems for remotely piloted, dynamically-scaled research aircraft. Current calibration methods were deemed not practical for this application because of confined test range size and limited flight time available for each sortie. A method was developed that uses high data rate measurements of static and total pressure, and GPSbased ground speed measurements to compute the pressure errors over a range of airspeed. The novel application of this approach is the use of system identification methods that rapidly compute optimal pressure error models with defined confidence intervals in nearreal time. This method has been demonstrated in flight tests and has shown 2- bounds of approximately 0.2 kts with an order of magnitude reduction in test time over other methods. As part of this experiment, a unique database of wind measurements was acquired concurrently with the flight experiments, for the purpose of experimental validation of the optimization method. This paper describes the GPS-based pitot-static calibration method developed for the AirSTAR research test-bed operated as part of the Integrated Resilient Aircraft Controls (IRAC) project in the NASA Aviation Safety Program (AvSP). A description of the method will be provided and results from recent flight tests will be shown to illustrate the performance and advantages of this approach. Discussion of maneuver requirements and data reduction will be included as well as potential applications.

Foster, John V.↗
NASA NTRS2015

NASA Affordable Vehicle Avionics (AVA): Common Modular Avionics System for Nano-Launchers Offering Affordable Access to Space

Small satellites are becoming ever more capable of performing valuable missions for both government and commercial customers. However, currently these satellites can only be launched affordably as secondary payloads. This makes it difficult for the small satellite mission to launch when needed, to the desired orbit, and with acceptable risk. NASA Ames Research Center has developed and tested a prototype low-cost avionics package for space launch vehicles that provides complete GNC functionality in a package smaller than a tissue box with a mass less than 0.84 kg. AVA takes advantage of commercially available, low-cost, mass-produced, miniaturized sensors, filtering their more noisy inertial data with realtime GPS data. The goal of the Advanced Vehicle Avionics project is to produce and flight-verify a common suite of avionics and software that deliver affordable, capable GNC and telemetry avionics with application to multiple nano-launch vehicles at 1 the cost of current state-of-the-art avionics.

Guidance Navigation and Control↗