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Caltech's Jet Propulsion Laboratory (JPL) has been processing digital image data returned from remote sensing instruments on spacecraft sine the Mariner 4 spacecraft flew by Mars in 1964.
Digital image-processing techniques have been used to analyze a variety of geophysical and geochemical map data covering southern Missouri, a region with important basement and strata-bound mineral deposits. Gravity and magnetic anomaly patterns, which have been reformatted to image displays, indicate a deep crustal structure cutting northwest-southeast through southern Missouri. In addition, geologic map data, topography, and Landsat multispectral scanner images have been used as base maps for the digital overlay of aerial gamma-ray and stream sediment chemical data for the 1 x 2-deg Rolla quadrangle. Results indicate enrichment of a variety of elements within the clay-rich alluvium covering many of the interfluvial plains, as well as a complicated pattern of enrichment for the sedimentary units close to the Precambrian rhyolites and granites of the St. Francois Mountains.
Digital computer processing of visible and reflective infrared scanner data for automatic computer mapping of Yellowstone National Park
A new airborne Linear Array Pushbroom Radiometer (LAPR-II) was built. LAPR-II will use linear arrays of silicon detectors to acquire four channels of digital image data for spectral bands within the visible and near infrared portions of the spectrum (0.4 - 1.0 micrometers). The data will be quantized to 10 bits, and spectral filters for each channel will be changeable in flight. The instrument will initially be flown aboard a NASA/Wallops' aircraft, and off nadir pointing of LAPR-II will be possible. Together, the instrument and its platform will provide a flexible readily available source of digital image data for scientific experiments. If LAPR-II is to serve as a precise scientific instrument, the instrument's characteristics must be quantitatively described and the data must be calibrated with respect to absolute radiometric units. The LAPR-II is described and the work required to characterize the instrument's spectral response, radiometric response, and spatial resolution and to calibrate the response from the many detectors per array is outlined.
The author has identified the following significant results. Efforts to provide data processing support for ERTS-1 investigators in Kansas are summarized. Programs have been developed for data retrieval, feature extraction, and classification of digital MSS data. The IDECS/PDP-15 facility at the University of Kansas Remote Sensing Laboratory has been used for quick look analysis of ERTS-1 imagery. Programs have been developed for studying fresh water bodies in ERTS-1 imagery over Kansas on the IDECS.
The author has identified the following significant results. The DCS water-stage data from the USGS streamflow gaging station on the Verde River near Camp Verde furnished information sufficient for the accurate computation of daily mean streamflow rates during the first 2 months of operation. Daily mean flow rates computed from the DCS data agreed with those computed from the digital recorder data within + or - 5% during periods of stable or slowly changing flow and within + or - 10% during periods of rapidly changing high flow. The SRP was furnished near-real time DCS information on snow moisture content and streamflow rates for use in the management and operation of the multiple-use reservoir system. The SRP, by prudent water management and the use of near-real time hydrologic data furnished by microwave and ERTS DCS telemetry, was successful in anticipating the amount of flow into the Salt and Verde Rivers and in the subsequent release of water at rates that did not create flooding in metropolitan Phoenix. Only minor flooding occurred along the Gila River west of Phoenix. According to the Maricopa County Civil Defense agency, wage and salary losses of about $11,400,000 resulted from closing of roads across the Salt River in the winter and spring of 1972-73; however, the number and duration of the closing were minimized by use of DCS data.
The Transient Event Rejection for Acquisition and Tracking (TERAT) algorithm governs operation of image-data-acquisition and -processing system. TERAT processes digitized image data to acquire (that is, identify) candidate steady source of light, validate candidate source, and track validated source, all in presence of real or apparent luminous transients represented in image data. Source of light tracked could be star or distant luminous beacon. Transients caused by impacts of ionizing radiation on imaging array of photodetectors or by unsteady light sources not meant to be tracked. TERAT functions with limited data-processing resources. TERAT algorithm currently operational on NASA's TOPEX mission.
Modern digital avionic systems with distributed processing require networking to connect the many elements. Digital Autonomous Terminal Access Communication (DATAC) is one of many such networks. DATAC has been implemented on the Transport Systems Research Vehicle (TSRV), a Boeing 737 aircraft operated by the National Aeronautics and Space Administration's Advanced Transport Operating Systems Program Office (ATOPS). This paper presents the TSRV implementation of the DATAC bus, a description of the DATAC system, a synchronization mechanism, details of data flow throughout the system, and a discussion of the modes available with DATAC. Numerous flight tests have been conducted using DATAC as the only means of communication between systems with outstanding results. DATAC is now an integral part of the TSRV and is expected to satisfy near term as well as future requirements for growth and flexibility.
A matched pair of computer algorithms determines whether line of sight (LOS) is obstructed by terrain. These algorithms were originally designed for use in conjunction with combat-simulation software in military training exercises, but could also be used for such commercial purposes as evaluating lines of sight for antennas or determining what can be seen from a "room with a view." The quadtree preparation algorithm operates on an array of digital elevation data and only needs to be run once for a terrain region, which can be quite large. Relatively little computation time is needed, as each elevation value is considered only one and one-third times. The LOS assessment algorithm uses that quadtree to answer LOS queries. To determine whether LOS is obstructed, a piecewise-planar (or higher-order) terrain skin is computationally draped over the digital elevation data. Adjustments are made to compensate for curvature of the Earth and for refraction of the LOS by the atmosphere. Average computing time appears to be proportional to the number of queries times the logarithm of the number of elevation data points. Accuracy is as high as is possible for the available elevation data, and symmetric results are assured. In the simulation, the LOS query program runs as a separate process, thereby making more random-access memory available for other computations.
Photogrammetric analysis of high-speed digital video data was performed to estimate trajectories of foam debris ejected from an F-15B aircraft. This work was part of a flight test effort to study the transport properties of insulating foam shed by the Space Shuttle external tank during ascent. The conical frustum-shaped pieces of debris, called "divots," were ejected from a flight test fixture mounted underneath the F-15B aircraft. Two onboard cameras gathered digital video data at two thousand frames per second. Time histories of divot positions were determined from the videos post flight using standard photogrammetry techniques. Divot velocities were estimated by differentiating these positions with respect to time. Time histories of divot rotations were estimated using four points on the divot face. Estimated divot position, rotation, and Mach number for selected cases are presented. Uncertainty in the results is discussed.
Advanced methods were developed to determine time varying winds and turbulence from digital flight data recorders carried aboard modern airliners. Analysis of several cases involving severe clear air turbulence encounters at cruise altitudes has shown that the aircraft encountered vortex arrays generated by destabilized wind shear layers above mountains or thunderstorms. A model was developed to identify the strength, size, and spacing of vortex arrays. This model is used to study the effects of severe wind hazards on operational safety for different types of aircraft. The study demonstrates that small remotely piloted vehicles and executive aircraft exhibit more violent behavior than do large airliners during encounters with high-altitude vortices. Analysis of digital flight data from the accident at Dallas/Ft. Worth in 1985 indicates that the aircraft encountered a microburst with rapidly changing winds embedded in a strong outflow near the ground. A multiple-vortex-ring model was developed to represent the microburst wind pattern. This model can be used in flight simulators to better understand the control problems in severe microburst encounters.
Advanced methods were developed to determine time varying winds and turbulence from digital flight data recorders carried aboard modern airliners. Analysis of several cases involving severe clear air turbulence encounters at cruise altitudes has shown that the aircraft encountered vortex arrays generated by destabilized wind shear layers above mountains or thunderstorms. A model was developed to identify the strength, size, and spacing of vortex arrays. This model is used to study the effects of severe wind hazards on operational safety for different types of aircraft. It is demonstrated that small remotely piloted vehicles and executive aircraft exhibit more violent behavior than do large airliners during encounters with high-altitude vortices. Analysis of digital flight data from the accident at Dallas/Ft. Worth in 1985 indicates that the aircraft encountered a microburst with rapidly changing winds embedded in a strong outflow near the ground. A multiple-vortex-ring model was developed to represent the microburst wind pattern. This model can be used in flight simulators to better understand the control problems in severe microburst encounters.
Application of the digital signal processing technique of autoregressive-moving-average (ARMA) modeling to the estimation of power spectra and shock spectra from Space Shuttle lift-off flight accelerograms is described in this paper. The background for application to ARMA of lift-off accelerograms which are non-stationary in nature is exemplified through a step-by-step discussion of actual numerical results. Included is a discussion of pertinent mathematical background for the ARMA approximations. Potential areas for application of ARMA modeling in payload integration activities are suggested.
Experimental data frequently have a poor signal-to-noise ratio which one would like to enhance before analysis. With the data in digital form, this may be accomplished by means of a digital filter. A fast digital filter based upon the principle of least squares and using the techniques of convoluting integers is described. In addition to smoothing, this filter also is capable of accurately and simultaneously locating spectral peaks and shoulders. This technique has been adapted into a computer subroutine, and results of several test cases are shown, including mass spectral data and data from a proportional counter for the High Energy Astronomy Observatory.
Various digital enhancement techniques for SAR are compared using SIR-B and Seasat images of the Canadian Shield. The three best methods for enhancing geological structure were found to be: (1) a simple linear contrast stretch; (2) a mean or median low-pass filter to reduce speckle prior to edge enhancement or a K nearest-neighbor average to cosmetically reduce speckle; and (3) a modification of the Moore-Waltz (1983) technique. Three look directions were coregistered and several means of data display were investigated as means of compensating for radar azimuth biasing.
A high pressure, high-temperature turbine test facility constructed for use in turbine cooling research is described. Several recently developed temperature and pressure measuring techniques are used in this facility. The measurement techniques, their status, previous applications and some results are discussed. Noncontact surface temperature measurements are made by optical methods. Radiation pyrometry principles combined with photoelectric scanning are used for rotating components and infrared photography for stationary components. Contact (direct) temperature and pressure measurements on rotating components are expected to be handled with an 80 channel rotary data package which mounts on and rotates with the turbine shaft at speeds up to 17,500 rpm. The data channels are time-division multiplexed and converted to digital words in the data package. A rotary transformer couples power and digital data to and from the shaft.
A high pressure, high-temperature turbine test facility is being constructed at the NASA Lewis Research Center for use in turbine cooling research. Several recently developed temperature and pressure measuring techniques will be used in this facility. This paper describes these measurement techniques, their status, previous applications and some results. Noncontact surface temperature measurements will be made by optical methods. Radiation pyrometry principles combined with photoelectric scanning will be used for rotating components and infrared photography for stationary components. Contact (direct) temperature and pressure measurements on rotating components will be handled with an 80-channel rotary data package which mounts on and rotates with the turbine shaft at speeds up to 17,500 rpm. The data channels are time-division multiplexed and converted to digital words in the data package. A rotary transformer couples power and digital data to and from the shaft.
This report is a deliverable for the “Final Report” task of DOE NEET Project 19-16790, "Context-Aware Safety Information Display for Nuclear Field Workers." This project's overall goal is to test the hypothesis that integrating computer vision and process reasoning methods will enable proactive visualization of the safe operation and maintenance processes of Nuclear Power Plants (NPP) for field workers. Augmented Reality (AR) glasses adopting such proactive safety information visualization techniques can significantly increase personnel safety and reduce the NPP’s operating costs. The current practice of monitoring NPPs requires workers to switch between digital models, data, and physical workspaces in identifying relevant but potentially occluded objects and in assessing the risks of operation and maintenance processes. On the other hand, frequently changed field conditions require field workers to report to supervisors for real-time guidance. Such guidance is essential to ensure that changing conditions will not invalidate or endanger the work order and other ongoing processes that may jeopardize NPP operations. Additionally, incorrect recognition of equipment objects can result in communication errors and safety problems. AR techniques can assist engineers in viewing the physical workspaces with objects labeled with detailed operation procedures and safety reminders during field operations. The project team developed an “Intelligent Context-Aware Safety Information Display” (ICAD) for supporting Nuclear Power Plant (NPP) field workers in achieving safe and efficient execution of a series of operational tasks in uncertain and changing workspaces of an NPP. Before designing the ICAD-AR prototype, the project team synthesized NPP operational knowledge models through literature review studies, surveys, interviews with domain experts, and knowledge modeling. The project team conducted an extensive study of the operational procedures of various NPPs, and digital technologies that can support the safe and efficient execution of those procedures in different NPP operational contexts. This literature review helped the project team conduct surveys and interviews with nuclear engineers and field workers to identify three categories of information. The NPP knowledge modeling efforts reveal that the three categories of information identified have different levels of importance in a typical procedure of carrying out a series of tasks to achieve a specific NPP operation goal (e.g., shutdown, mode changes). These three categories of information include 1) Workspace dynamics – the changing spatial arrangements of workspaces, tools, protection equipment, and supporting materials, 2) Workflow prognostics – the dynamic dependencies between different parts of an NPP that functionally support and influence each other in terms of safety and efficiency, and 3) Hazards – objects and spaces that contain hazardous materials or physical conditions that can pose risks to workers or mechanical systems. The project team has profiled the importance levels of these categories of information into a knowledge model. This knowledge model specifies what types of information are more critical for a given task in a given workspace so that computers can automatically identify critical objects and sensors in a scene for delivering context-ware safety information to field workers through AR devices. Significant research development of this project results in technical research outcomes and a prototyping system that illustrates the technical feasibility of establishing an ICAD-AR system supporting the proactive safety information display for nuclear field workers. This final report summarizes the project team’s technological achievements in the past three years. Overall, the project team completed the development and integration of five techniques into a prototype ICAD Augmented Reality (ICAD-AR) system and demonstrated the developed system’s real-time execution in a mechanical room. The project team completed the analysis of using this prototype in other types of workspaces based on 3D image data and digital design models collected from two additional workspaces (a water treatment plant and a flow loop training facility). The integrated techniques include 1) Natural Language Processing (NLP) algorithms supporting the generation and updates of nuclear fieldwork process models based on text analysis of work packages and operation manuals; 2) sensor log analysis for predicting control actions in given sensor reading contexts; 3) computer vision algorithms for automatic localization and navigation of workers; 4) object detection algorithms for identifying task-related objects and correlated sensors for safety checking; 5) AR technique as a platform for supporting the integration. The testing results of these five techniques have shown that 1) the sensor log analysis model can predict the next control action with an accuracy of 0.883; 2) the trained natural language processing model can extract more than 80% of the critical information from paper-based procedures (PBPs); 3) the navigation algorithm with the integration of Visual Inertial Odometry (VIO) and Non-Recursive Bayesian Filter methods make operator’s trajectory estimation resilient to drift error; 4) the computer vision algorithm can detect task-specific and safety-critical objects with an average accuracy of 95.3%. The project team used work procedures collected from a flow loop training facility and two datasets collected from two mechanical rooms simulating the workspaces of NPPs to demonstrate the technical capabilities of the developed ICAD-AR prototype. The demonstration validated the technical feasibility of establishing the ICAD-AR system for nuclear field workers and identified the challenges in 1) automatic text analysis of work packages; 2) use of limited samples of sensor logs for predicting the proper timings of control actions; 3) reliably tracking workers and their task progress in mechanical rooms with many similar objects.