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At least 415 records · Page 23

Design Description of the X-33 Avionics Architecture

In this paper, we provide a design description of the X-33 avionics architecture. The X-33 is an autonomous Single Stage to Orbit (SSTO) launch vehicle currently being developed by Lockheed Martin for NASA as a technology demonstrator for the VentureStar Reusable Launch Vehicle (RLV). The X-33 avionics provides autonomous control of die vehicle throughout takeoff, ascent, descent, approach, landing, rollout, and vehicle safing. During flight the avionics provides communication to the range through uplinked commands and downlinked telemetry. During pre-launch and post-safing activities, the avionics provides interfaces to ground support consoles that perform vehicle flight preparations and maintenance. The X-33 Avionics is a hybrid of centralized and distributed processing elements connected by three dual redundant Mil-Std 1553 data buses. These data buses are controlled by a central processing suite located in the avionics bay and composed of triplex redundant Vehicle Mission Computers (VMCs). The VMCs integrate mission management, guidance, navigation, flight control, subsystem control and redundancy management functions. The vehicle sensors, effectors and subsystems are interfaced directly to the centralized VMCs as remote terminals or through dual redundant Data Interface Units (DIUs). The DIUs are located forward and aft of the avionics bay and provide signal conditioning, health monitoring, low level subsystem control and data interface functions. Each VMC is connected to all three redundant 1553 data buses for monitoring and provides a complete identical data set to the processing algorithms. This enables bus faults to be detected and reconfigured through a voted bus control configuration. Data is also shared between VMCs though a cross channel data link that is implemented in hardware and controlled by AlliedSignal's Fault Tolerant Executive (FTE). The FTE synchronizes processors within the VMC and synchronizes redundant VMCs to each other. The FTE provides an output-voting plane to detect, isolate and contain faults due to internal hardware or software faults and reconfigures the VMCs to accommodate these faults. Critical data in the 1553 messages are scheduled and synchronized to specific processing frames in order to minimize data latency. In order to achieve an open architecture, military and commercial off-the-shelf equipment is incorporated using common processors, standard VME backplanes and chassis, the VxWorks operating system, and MartixX for automatic code generation. The use of off-the-shelf tools and equipment helps reduce development time and enables software reuse. The open architecture allows for technology insertion, while the distributed modular elements allow for expansion to increased redundancy levels to meet the higher reliability goals of future RLVs.

Reichenfeld, Curtis J.↗

ULTOR(Registered TradeMark) Passive Pose and Position Engine For Spacecraft Relative Navigation

The ULTOR(Registered TradeMark) Passive Pose and Position Engine (P3E) technology, developed by Advanced Optical Systems, Inc (AOS), uses real-time image correlation to provide relative position and pose data for spacecraft guidance, navigation, and control. Potential data sources include a wide variety of sensors, including visible and infrared cameras. ULTOR(Registered TradeMark) P3E has been demonstrated on a number of host processing platforms. NASA is integrating ULTOR(Registerd TradeMark) P3E into its Relative Navigation System (RNS), which is being developed for the upcoming Hubble Space Telescope (HST) Servicing Mission 4 (SM4). During SM4 ULTOR(Registered TradeMark) P3E will perform realtime pose and position measurements during both the approach and departure phases of the mission. This paper describes the RNS implementation of ULTOR(Registered TradeMark) P3E, and presents results from NASA's hardware-in-the-loop simulation testing against the HST mockup.

Hannah, S. Joel↗

Rapid Development of the Seeker Free-Flying Inspector Guidance, Navigation, and Control System

Seeker is an automated extravehicular free-flying inspector CubeSat designed and built in-house at the Johnson Space Center (JSC). As a Class 1E project funded by the International Space Station (ISS) Program, Seeker had a streamlined process to flight certification, but the vehicle had to be designed, developed, tested, and delivered within approximately one year after authority to pro-ceed (ATP) and within a $1.8 million budget. These constraints necessitated an expedited Guidance, Navigation, and Control (GNC) development schedule, development began with a navigation sensor trade study using Linear Covariance (LinCov) analysis and a rapid sensor downselection process, resulting in the use of commercial off-the-shelf (COTS) sensors which could be procured quickly and subjected to in-house environmental testing to qualify them for flight. A neural network was used to enable a COTS camera to provide bearing measurements for visual navigation. The GNC flight software (FSW) algorithms utilized lean development practices and leveraged the Core Flight Software (CFS) architecture to rapidly develop the GNC system, tune the system parameters, and verify performance in simulation. This pace was anchored by several Hardware-Software Integration (HSI) milestones, which forced the Seeker GNC team to develop the interfaces both between hardware and software and between the GNC domains early in the project and to enable a timely delivery.

Sullivan, Jacob↗

Rapid Development of the Seeker Free-Flying Inspector Guidance, Navigation, and Control System

Seeker is an automated extravehicular free-flying inspector CubeSat designed and built in-house at the Johnson Space Center (JSC). As a Class 1E project funded by the International Space Station (ISS) Program, Seeker had a stream-lined process to flight certification, but the vehicle had to be designed, developed, tested, and delivered within approximately one year after authority to proceed (ATP) and within a $1.8 million budget. These constraints necessitated an expedited Guidance, Navigation, and Control (GNC) development schedule. Development began with a navigation sensor trade study using Linear Covariance (LinCov) analysis and a rapid sensor down-selection process, resulting in the use of commercial off-the-shelf (COTS) sensors which could be procured quickly and subjected to in-house environmental testing to qualify them for flight. A neural network was used to enable a COTS camera to provide bearing measure-ments for visual navigation. The GNC flight software (FSW) algorithms utilized lean development practices and leveraged the Core Flight Software (CFS) architecture to rapidly develop the GNC system, tune the system parameters, and verify performance in simulation. This pace was anchored by several Hardware-Software Integration (HSI) milestones, which forced the Seeker GNC team to develop the interfaces both between hardware and software and between the GNC domains early in the project and to enable a timely delivery.

Sullivan, Jake↗

Space Technology Mission Directorate Game Changing Development Program

SPLICE project annual program review presentation. SPLICE Precision Landing and Hazard Avoidance (PL&HA) technologies will improve landing precision by an order of magnitude and enable high-resolution real-time 3-D mapping for hazard detection and avoidance during descent.

Guidance Navigation and Control↗

Development of Micro Air Reconnaissance Vehicle as a Test Bed for Advanced Sensors and Electronics

This paper describes the development of a Micro/Mini Air Reconnaissance Vehicle for advanced sensors and electronics at NASA Langley Research Center over the last year. This vehicle is expected to have a total weight of less than four pounds, a design velocity of 40 mph, an endurance of 15-20 minutes, and a maximum range of 5km. The vehicle has wings that are simple to detach yet retain the correct alignment. The upper fuselage surface has a quick release hatch used to access the interior and also to mount the varying propulsion systems. The sensor suite developed for this vehicle consists of a Pitot-static measurement system for determining air speed, an absolute pressure measurement for determining altitude, magnetic direction measurement, and three orthogonal gyros to determine body angular rates. Swarming GPS-guidance and in-flight maneuvering is discussed, as well as design and installation of some other advance sensors like MEMS microphones, infrared cameras, GPS, humidity sensors, and an ultrasonic sonar sensor. Also low cost, small size, high performance control and navigation system for the Micro Air Vehicle is discussed. At the end, laboratory characterization of different sensors, motors, propellers, and batteries will be discussed.

Shams, Qamar A.↗

Engineering a visual system for seeing through fog

We examine the requirements for on-board aircraft sensor systems that would allow pilots to 'see through' poor weather, especially fog, and land and rollout aircraft under conditions that currently cause flight cancellations and airport closures. Three visual aspects of landing and rollout are distinguished: guidance, hazard detection and hazard recognition. The visual features which support the tasks are discussed. Three broad categories of sensor technology are examined: passive millimeter wave (PMMW), imaging radar, and passive infrared (IR). PMMW and imaging radar exhibit good weather penetration, but poor spatial and temporal resolution. Imaging radar exhibits good weather penetration, but typically relies on a flat-earth assumption which can lead to interpretive errors. PMMW systems have a narrow field of view. IR has poorer weather penetration but good spatial resolution. We recommend using both millimeter-wave and infrared sensor systems, blending the images using multiresolution digital-image pyramid-processing technology, and fusing the resulting real-time images with stored database imagery of the same scene.

Larimer, J.↗

User's guide to the Fault Inferring Nonlinear Detection System (FINDS) computer program

Described are the operation and internal structure of the computer program FINDS (Fault Inferring Nonlinear Detection System). The FINDS algorithm is designed to provide reliable estimates for aircraft position, velocity, attitude, and horizontal winds to be used for guidance and control laws in the presence of possible failures in the avionics sensors. The FINDS algorithm was developed with the use of a digital simulation of a commercial transport aircraft and tested with flight recorded data. The algorithm was then modified to meet the size constraints and real-time execution requirements on a flight computer. For the real-time operation, a multi-rate implementation of the FINDS algorithm has been partitioned to execute on a dual parallel processor configuration: one based on the translational dynamics and the other on the rotational kinematics. The report presents an overview of the FINDS algorithm, the implemented equations, the flow charts for the key subprograms, the input and output files, program variable indexing convention, subprogram descriptions, and the common block descriptions used in the program.

Caglayan, A. K.↗

Independent Orbiter Assessment (IOA): Analysis of the guidance, navigation, and control subsystem

The results of the Independent Orbiter Assessment (IOA) of the Failure Modes and Effects Analysis (FMEA) and Critical Items List (CIL) is presented. The IOA approach features a top-down analysis of the hardware to determine failure modes, criticality, and potential critical items. To preserve independence, this analysis was accomplished without reliance upon the results contained within the NASA FMEA/CIL documentation. The independent analysis results corresponding to the Orbiter Guidance, Navigation, and Control (GNC) Subsystem hardware are documented. The function of the GNC hardware is to respond to guidance, navigation, and control software commands to effect vehicle control and to provide sensor and controller data to GNC software. Some of the GNC hardware for which failure modes analysis was performed includes: hand controllers; Rudder Pedal Transducer Assembly (RPTA); Speed Brake Thrust Controller (SBTC); Inertial Measurement Unit (IMU); Star Tracker (ST); Crew Optical Alignment Site (COAS); Air Data Transducer Assembly (ADTA); Rate Gyro Assemblies; Accelerometer Assembly (AA); Aerosurface Servo Amplifier (ASA); and Ascent Thrust Vector Control (ATVC). The IOA analysis process utilized available GNC hardware drawings, workbooks, specifications, schematics, and systems briefs for defining hardware assemblies, components, and circuits. Each hardware item was evaluated and analyzed for possible failure modes and effects. Criticality was assigned based upon the severity of the effect for each failure mode.

Trahan, W. H.↗

Scene segmentation of natural images using texture measures and back-propagation

Knowledge of the three-dimensional world is essential for many guidance and navigation applications. A sequence of images from an electro-optical sensor can be processed using optical flow algorithms to provide a sparse set of ranges as a function of azimuth and elevation. A natural way to enhance the range map is by interpolation. However, this should be undertaken with care since interpolation assumes continuity of range. The range is continuous in certain parts of the image and can jump at object boundaries. In such situations, the ability to detect homogeneous object regions by scene segmentation can be used to determine regions in the range map that can be enhanced by interpolation. The use of scalar features derived from the spatial gray-level dependence matrix for texture segmentation is explored. Thresholding of histograms of scalar texture features is done for several images to select scalar features which result in a meaningful segmentation of the images. Next, the selected scalar features are used with a neural net to automate the segmentation procedure. Back-propagation is used to train the feed forward neural network. The generalization of the network approach to subsequent images in the sequence is examined. It is shown that the use of multiple scalar features as input to the neural network result in a superior segmentation when compared with a single scalar feature. It is also shown that the scalar features, which are not useful individually, result in a good segmentation when used together. The methodology is applied to both indoor and outdoor images.

Sridhar, Banavar↗

Return to Flight: Crew Activities Resource Reel 1 of 2

The crew of the STS-114 Discovery Mission is seen in various aspects of training for space flight. The crew activities include: 1) STS-114 Return to Flight Crew Photo Session; 2) Tile Repair Training on Precision Air Bearing Floor; 3) SAFER Tile Inspection Training in Virtual Reality Laboratory; 4) Guidance and Navigation Simulator Tile Survey Training; 5) Crew Inspects Orbital Boom and Sensor System (OBSS); 6) Bailout Training-Crew Compartment; 7) Emergency Egress Training-Crew Compartment Trainer (CCT); 8) Water Survival Training-Neutral Buoyancy Lab (NBL); 9) Ascent Training-Shuttle Motion Simulator; 10) External Tank Photo Training-Full Fuselage Trainer; 11) Rendezvous and Docking Training-Shuttle Engineering Simulator (SES) Dome; 12) Shuttle Robot Arm Training-SES Dome; 13) EVA Training Virtual Reality Lab; 14) EVA Training Neutral Buoyancy Lab; 15) EVA-2 Training-NBL; 16) EVA Tool Training-Partial Gravity Simulator; 17) Cure in Place Ablator Applicator (CIPAA) Training Glove Vacuum Chamber; 16) Crew Visit to Merritt Island Launch Area (MILA); 17) Crew Inspection-Space Shuttle Discovery; and 18) Crew Inspection-External Tank and Orbital Boom and Sensor System (OBSS). The crew are then seen answering questions from the media at the Space Shuttle Landing Facility.

Source record↗

An Overview of the Smart Sensor Inter-Agency Reference Testbench (SSIART)

In this paper, we present an overview of a proposed collaboration between the National Aeronautics and Space Administration (NASA) and the European Space Agency (ESA), which is designed to facilitate the introduction of commercial-off-the-shelf (COTS) radios for smart-sensing applications into international spaceflight programs and projects. The proposed work will produce test hardware reference designs, test software reference architectures and example implementations, test plans in reference test environments, and test results, all of which will be shared between the agencies and documented for future use by mission planners. The proposed collaborative structure together with all of the anticipated tools and results produced under the effort is collectively referred to as the Smart Sensor Inter-agency Reference Testbench or SSIART. It is intended to provide guidance in technology selection and in increasing the related readiness levels of projects and missions as well as the space industry.

Wagner, Raymond S.↗

Autonomous docking ground demonstration

The Autonomous Docking Ground Demonstration is an evaluation of the laser sensor system to support the docking phase (12 ft to contact) when operated in conjunction with the guidance, navigation, and control (GN&C) software. The docking mechanism being used was developed for the Apollo/Soyuz Test Program. This demonstration will be conducted using the 6-DOF Dynamic Test System (DTS). The DTS simulates the Space Station Freedom as the stationary or target vehicle and the Orbiter as the active or chase vehicle. For this demonstration, the laser sensor will be mounted on the target vehicle and the retroflectors will be on the chase vehicle. This arrangement was chosen to prevent potential damage to the laser. The laser sensor system, GN&C, and 6-DOF DTS will be operated closed-loop. Initial conditions to simulate vehicle misalignments, translational and rotational, will be introduced within the constraints of the systems involved.

Lamkin, Steve L.↗

Assessment of MODIS Reflected Solar Calibration Uncertainty

Determination of the calibration accuracy and traceability of a remote sensing instrument is a driving issue in the use of satellite data for calibration inter-comparisons and studying climate change. The Terra and Aqua MODerate Resolution Imaging Spectroradiometer (MODIS) instruments have successfully operated for more than 11 and 9 years, respectively. Twenty of the thirty six MODIS spectral bands are in the reflected solar region with center wavelengths ranging from 0.41 to 2.2 microns. MODIS reflective solar band (RSB) on-orbit calibration is reflectance based through the use of an on-board solar diffuser (SO). The calibration uncertainty requirements are +/-2.0% for the RSB reflectance factors at sensor specified typical scene reflectances or radiances. The SO bi-directional reflectance factor (BRF) was characterized pre-launch and its on-orbit changes are tracked by an on-board solar diffuser stability monitor (SDSM). This paper provides an assessment of MODIS RSB on-orbit calibration traceability and uncertainty for its Level 1B (L1B) reflectance factors. It examines in details each of the uncertainty contributors, including those from pre-launch measurements as well as on-orbit observations. Common challenging issues and differences due to individual sensors' specific characteristics and on-orbit performance are also discussed in this paper. Guidance and recommendations are presented, based on lessons from MODIS RSB calibration uncertainty assessment, for the development of future instrument calibration and validation plans.

Xiong, Xiaoxiong↗

NASA Tech Briefs, February 2012

This issue contains the following briefs: (1) Optical Comb from a Whispering Gallery Mode Resonator for Spectroscopy and Astronomy Instruments Calibration (2) Real-Time Flight Envelope Monitoring System (3) Nemesis Autonomous Test System (4) Mirror Metrology Using Nano-Probe Supports (5) Automated Lab-on-a-Chip Electrophoresis System (6) Techniques for Down-Sampling a Measured Surface Height Map for Model Validation (7) Multi-Component, Multi-Point Interferometric Rayleigh/Mie Doppler Velocimeter (8) Frequency to Voltage Converter Analog Front-End Prototype (9) Dust-Tolerant Intelligent Electrical Connection System (10) Gigabit Ethernet Asynchronous Clock Compensation FIFO (11) High-Speed, Multi-Channel Serial ADC LVDS Interface for Xilinx Virtex-5 FPGA (12) Glovebox for GeoLab Subsystem in HDU1-PEM (13) Modified Process Reduces Porosity when Soldering in Reduced Gravity Environments (14) Use of Functionalized Carbon Nanotubes for Covalent Attachment of Nanotubes to Silicon (15) Flexible Plug Repair for Shuttle Wing Leading Edge (16) Three Dimensionally Interlinked, Dense, Solid Form of Single-Walled CNT Ropes (17) Axel Robotic Platform for Crater and Extreme Terrain Exploration (18) Site Tamper and Material Plow Tool - STAMP (19) Magnetic Interface for Segmented Mirror Assembly (20) Transpiration-Cooled Spacecraft-Insulation-Repair Fasteners (21) Fluorescence-Based Sensor for Monitoring Activation of Lunar Dust (22) Aperture Ion Source (23) Virtual Ultrasound Guidance for Inexperienced Operators (24) Model-Based Fault Diagnosis: Performing Root Cause and Impact Analyses in Real Time (25) Interactive Schematic Integration Within the Propellant System Modeling Environment (26) Magnetic and Electric Field Polarizations of Oblique Magnetospheric Chorus Waves (27) Variable Sampling Mapping.

Source record↗

Applied Meteorology Unit (AMU) Quarterly Report Third Quarter FY-08

This report summarizes the Applied Meteorology Unit (AMU) activities for the third quarter of Fiscal Year 2008 (April - June 2008). Tasks reported on are: Peak Wind Tool for User Launch Commit Criteria (LCC), Anvil Forecast Tool in AWIPS Phase II, Completion of the Edward Air Force Base (EAFB) Statistical Guidance Wind Tool, Volume Averaged Height Integ rated Radar Reflectivity (VAHIRR), Impact of Local Sensors, Radar Scan Strategies for the PAFB WSR-74C Replacement, VAHIRR Cost Benefit Analysis, and WRF Wind Sensitivity Study at Edwards Air Force Base

Bauman, William↗

Testing Results of the X-38 Crew Return Vehicle GPS Receiver

The X-38 Crew Return Vehicle (CRV) utilizes a Space Integrated GPS/INS (SIGI) sensor to obtain navigation and attitude knowledge. Testing and analysis at the NASA Goddard Space Flight Center Guidance, Navigation, and Control's GPS Lab was conducted in order to validate the development of SIGI GPS receiver attitude firmware. The modifications to the International Space Station (ISS) SIGI receiver that were completed to meet the CRV requirements will be presented. The CRV is designed to be used as a life-boat in case of an emergency evacuation from the ISS. The need to return the ISS crew in a timely manner places challenging performance requirements on the SIGI sensor. This paper will summarize the performance of the SIGI GPS receiver for the CRV. The ability to track the GPS signals at any initial attitude and the performance of the SIGI GPS-only solution during reentry are detailed in this paper. A discussion regarding the use of the Global Satellite Systems GPS Signal Generator in testing the SIGI sensor will provide insight into the GPS validation process used at NASA Goddard.

Simpson, James↗