Real-Time Image Processing in Support of Aerial Sensing Applications
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A description is given of the NASA developed all-weather ice information system for the Great Lakes winter navigation program. The system utilizes an X-band side looking airborne radar (SLAR) for determining type, location, and areal distribution of the ice cover in the Great Lakes and an airborne, S band, down looking short pulse radar for obtaining ice thickness. Digitized SLAR data are relayed in real time via the NOAA-GOES satellite in geosynchronous orbit. The SLAR images along with hand drawn interpretative ice charts for various Great Lakes winter shipping areas are broadcast to facsimile recorders aboard vessles is the area via the MARAD marine VHF-FM radio network. These data assist such vessels in navigating both through and around the ice.
NASA is developing solar sail propulsion for a near-term Near Earth Asteroid (NEA) reconnaissance mission that will lay the groundwork for the future use of solar sails. The NEA Scout mission will use the sail as primary propulsion allowing it to survey and image one NEA's of interest for future human exploration. NEA Scout will launch on the first mission of the Space Launch System (SLS) in 2018. After its first encounter with the Moon, NEA Scout will enter the sail characterization phase by the 86 square meter sail deployment. A mechanical Active Mass Translation (AMT) system, combined with the remaining ACS propellant, will be used for sail momentum management. The spacecraft will perform a series of lunar flybys to achieve optimum departure trajectory before beginning its two year-long cruise. About one month before the asteroid flyby, NEA Scout will start its approach phase using optical navigation on top of radio tracking. The solar sail will provide NEA Scout continuous low thrust to enable a relatively slow flyby of the target asteroid under lighting conditions favorable to geological imaging. Once complete, NASA will have demonstrated the capability to fly low-cost, high delta V CubeSats to perform interplanetary missions.
The ability of lidar technology to provide three-dimensional elevation maps of the terrain, high precision distance to the ground, and approach velocity can enable safe landing of robotic and manned vehicles with a high degree of precision. Currently, NASA is developing novel lidar sensors aimed at needs of future planetary landing missions. These lidar sensors are a 3-Dimensional Imaging Flash Lidar, a Doppler Lidar, and a Laser Altimeter. The Flash Lidar is capable of generating elevation maps of the terrain that indicate hazardous features such as rocks, craters, and steep slopes. The elevation maps collected during the approach phase of a landing vehicle, at about 1 km above the ground, can be used to determine the most suitable safe landing site. The Doppler Lidar provides highly accurate ground relative velocity and distance data allowing for precision navigation to the landing site. Our Doppler lidar utilizes three laser beams pointed to different directions to measure line of sight velocities and ranges to the ground from altitudes of over 2 km. Throughout the landing trajectory starting at altitudes of about 20 km, the Laser Altimeter can provide very accurate ground relative altitude measurements that are used to improve the vehicle position knowledge obtained from the vehicle navigation system. At altitudes from approximately 15 km to 10 km, either the Laser Altimeter or the Flash Lidar can be used to generate contour maps of the terrain, identifying known surface features such as craters, to perform Terrain relative Navigation thus further reducing the vehicle s relative position error. This paper describes the operational capabilities of each lidar sensor and provides a status of their development. Keywords: Laser Remote Sensing, Laser Radar, Doppler Lidar, Flash Lidar, 3-D Imaging, Laser Altimeter, Precession Landing, Hazard Detection
This paper introduces a spatial pattern recognition processing concept involving the use of spectral feature classification technology and coherent optical correlation. The concept defines a hybrid image processing system incorporating both digital and optical technology. The hybrid instrument provides simplified pseudopattern images as functions of pixel classification from information embedded within a real-scene image. These pseudoimages become simplified inputs to an optical correlator for use in a subsequent pattern identification decision useful in executing landmark pointing, tracking, or navigating functions. Real-time classification is proposed as a research tool for exploring ways to enhance input signal-to-noise ratio as an aid in improving optical correlation. The approach can be explored with developing technology, including a current NASA Langley Research Center technology plan that involves a series of related Shuttle-borne experiments. A first-planned experiment, Feature Identification and Location Experiment (FILE), is undergoing final ground testing, and is scheduled for flight on the NASA Shuttle (STS2/flight OSTA-1) in 1980. FILE will evaluate a technique for autonomously classifying earth features into the four categories: bare land; water; vegetation; and clouds, snow, or ice.
Several researchers have proposed and implemented various systems pertaining to the development of autonomous land vehicles (ALVs). One fundamental problem associated with the navigation of an ALV is the ability to efficiently extract the boundaries of the pathway that need to be navigated. In this paper a method is presented that will determine the road boundaries in one pass using a limited search area in the input image. The method employs the statistical information regarding the gray levels present in the images along with geometrical constraints concerning the road. Some examples are given to demonstrate the efficacy of the method.
One goal of the "Demo III" unmanned ground vehicle program is to enable autonomous nighttime navigation at speeds of up to 10 m.p.h. To perform obstacle detection at night with stereo vision will require night vision cameras that produce adequate image quality for the driving speeds, vehicle dynamics, obstacle sizes, and scene conditions that will be encountered. This paper analyzes the suitability of four classes of night vision cameras (3-5 micrometer cooled FLIR, 8-12 micrometer cooled FLIR, 8-12 micrometer uncooled FLIR, and image intensifiers) for night stereo vision, using criteria based on stereo matching quality, image signal to noise ratio, motion blur and synchronization capability. We find that only cooled FLIRs will enable stereo vision performance that meets the goals of the Demo III program for nighttime autonomous mobility.
Future lander missions will travel to ambitious, scientifically interesting locations near rough and dangerous terrain. They will need to operate with limited prior information about the terrain, and under varying lighting conditions. Landing safely and precisely in the face of these challenges is difficult for existing vision-based landing systems, which require detailed orbital reconnaissance, a priori hazard maps, and impose time-of-day restrictions on landing to ensure similar lighting conditions in orbital and descent imagery. Advanced 3D imaging LiDAR systems currently under development, and originally intended for single-scan hazard detection, have the potential to be operated continuously from altitudes of up to 5 km. Used together with existing inertial measurement units (IMUs), these sensors open a path-to-flight for a full navigation and mapping system, which could replace or augment a traditional landing sensor suite. A landing system based around these sensors can perform accurate altimetry, map-relative localization (MRL), LiDAR-inertial odometry, and map refinement in an illumination-insensitive manner, over unknown or partially known terrain. This paper outlines preliminary work on a LiDAR-inertial landing system that: estimates the spacecraft trajectory during entry, descent, and landing (EDL); and maps the topography of the terrain below, for future use in hazard detection and avoidance. An incremental, factor graph based, smoothing approach is used to solve for the maximum a posteriori trajectory of spacecraft states. Integrated IMU measurements and features tracked in adjacent range and intensity images are used to estimate motion (LiDAR-inertial odometry). LiDAR scans are binned into motion-corrected digital elevation models (DEMs), which are matched to an existing orbital topographic map to provide absolute position information (MRL). The estimated trajectory is then used to project the LiDAR scans into the map frame, creating a variable-resolution quadtree topographic map suitable for hazard detection and avoidance. Existing topographic maps from throughout the solar system (i.e., Earth, the Moon, Mars, Ceres, Vesta, Europa, Enceladus, and Eros) are upsampled for use in EDL simulations. The Mars 2020 Lander Vision System Simulator (LVSS) is extended to simulate LiDAR-inertial data for realistic EDL trajectories. Results of the algorithm operating on the simulated data are presented. Estimated spacecraft trajectory and refined map are compared to ground truth to assess estimation accuracy.
This paper describes the target designation, tracking, approach, and camera handoff technologies required to achieve accurate, single-command autonomous instrument placement for a planetary rover. It focuses on robust tracking integrated with obstacle avoidance during the approach phase, and image-based camera handoff to allow vision-based instrument placement. It also provides initial results from a complete system combining these technologies with rover base placement to maximize arm manipulability and image-based instrument placement.
The Galileo spacecraft may be targeted for a close flyby of an asteroid on its way to an encounter with Jupiter. An orbit determination accuracy analysis was carried out for the case of the asteroid 29 Amphitrite based on the use of radio metric and optical data types. Prior to encounter, the uncertainty in the asteroid's position, based on astrometric observations from earth, amounts to several hundred kilometers. This ephemeris uncertainty constitutes the dominant error in the determination of the spacecraft orbit with respect to Amphitrite. It is shown that the spacecraft-asteroid relative position can be improved by imaging asteroid-star pairs with the Galileo charge-coupled device (CCD) camera, enabling an accurate flyby of the asteroid. The main benefit of optical navigation is to enable the instrument pointing updates necessary for closeup viewing of the asteroid. A discussion of the evolution of the target error ellipse parameters as a function of data coverage and various combinations of radiometric and optical data types is also presented.
Scientific exploration of Venus using an atmospheric probe requires relaying telemetry to Earth as the probe descends through the atmosphere to the surface of Venus. Using the flyby spacecraft to relay the probe telemetry to Earth will require precise carrier-to-probe pointing accuracy of the relay spacecraft’s antenna. NASA’s Deep Atmosphere Venus Investigation of Noble gases, Chemistry, and Imaging (DAVINCI) mission uses this carrier-to-probe relay technique. Although DAVINCI includes a coherent cross-link for science, this is not baselined for navigation tracking. This paper explores the potential effectiveness of cross-link tracking for reducing trajectory uncertainty and improving spacecraft-to-probe pointing.
The use of Synthetic Aperture Radar (SAR) data from the satellite ERS-1 to assist the French polar vessel 'L'Astrolabe' during its navigation through Artic sea ice in the Northeast Passage is reported. The ship spent one month on the voyage from Europe to Japan, and high resolution SAR images and ice maps based on SAR images from ERS-1 and Special Sensor Microwave/Imager were telefaxed to the ship using the Inmarsat system. The time delay from observation to the reception of SAR images aboard the ship varied from 6 hours to two days. The quality of these ice maps was compared with Russian ice maps and observations from the ship. The SAR imagery provided detailed information on ice floe distribution, ice concentration, ice types, open leads, and tracks in ice from icebreakers. The response from the Russian ice specialists on the quality of the SAR ice maps was very positive.
An algorithm for the optical computation of potential field maps suitable for mobile robot navigation is described and experimentally produced maps and paths are presented. The parallel analog optical computation employs a two-dimensional spatial light modulator on which an image of the potential field map is generated. Optically calculated fields contain no local minima, tend to produce paths centered in gaps between obstacles, and produce paths which give preference to wide gaps. Calculation of 128 x 128 pixel fields at a few hertz are possible with current technology, and calculation time vs. map size scales favorably in comparison to digital electronic computation.
The Center of Excellence (COE) was created nine years ago to facilitate active collaboration between the scientists at Ames Research Center and the Stanford Psychology Department. Significant interchange of ideas and personnel continues between Stanford and participating groups at NASA-Ames; the COE serves its function well. This progress report is organized into sections divided by project. Each section contains a list of investigators, a background statement, progress report, and a proposal for work during the coming year. The projects are: Algorithms for development and calibration of visual systems, Visually optimized image compression, Evaluation of advanced piloting displays, Spectral representations of color, Perception of motion in man and machine, Automation and decision making, and Motion information used for navigation and control.
This presentation briefly describes the Gravity Probe B (GP-B) Experiment which is designed to measure parts of Einstein's general theory of relativity by monitoring gyroscope orientation relative to a distant guide star. To measure the miniscule angles predicted by Einstein's theory, it was necessary to build near-perfect gyroscopes that were approximately 50 million times more precise than the best navigational gyroscopes. A telescope mounted along the central axis of the dewar and spacecraft provided the experiment's pointing reference to a guide star. The telescope's image divide precisely split the star's beam into x-axis and y-axis components whose brightness could be compared. GP-B's 650-gallon dewar, kept the science instrument inside the probe at a cryogenic temperature for 17.3 months and also provided the thruster propellant for precision attitude and translation control. Built around the dewar, the GP-B spacecraft was a total-integrated system, comprising both the space vehicle and payload, dedicated as a single entity to experimentally testing predictions of Einstein's theory.
Solar Cruiser is a Small Satellite Technology Demonstration Mission (TDM) to mature solar sail propulsion technology to enable near-term, high-priority breakthrough science missions as defined in the Solar and Space Physics Decadal Survey. Solar sails have the potential to provide high ΔV for many types of missions. Solar sails are large, mirror-like structures made of a lightweight material that reflects sunlight to propel the spacecraft. The continuous solar photon pressure provides thrust with no need for the heavy, expendable propellants used by conventional chemical and electric propulsion systems. Solar Cruiser will demonstrate a “sailcraft” platform with pointing control and attitude stability comparable to traditional platforms, upon which a new class of Heliophysics missions may fly. It will show sailcraft operation (acceleration, navigation, station keeping, heliocentric plane change) scalability of sail technologies such as the boom, membrane, and deployer to enable more demanding missions, such as high inclination solar imaging. Solar Cruiser will launch as a secondary payload with NASA’s Interstellar Mapping and Acceleration Probe (IMAP) in early 2025. The sailcraft will separate from the launch vehicle on a near-L1 trajectory (Sun-Earth Lagrangian Point 1; sunward of L1 along the Sun-Earth Line) and complete its primary mission in 11 months or less.
The National Aeronautics and Space Administration s (NASA) Lunar Reconnaissance Orbiter (LRO) launched on June 18, 2009 from the Cape Canaveral Air Force Station aboard an Atlas V launch vehicle and into a direct insertion trajectory to the oon. LRO, which was designed, built, and operated by the NASA Goddard Space Flight Center in Greenbelt, MD, is gathering crucial data on the lunar environment that will help astronauts prepare for long-duration lunar expeditions. The mission has a nominal life of 1 year as its seven instruments find safe landing sites, locate potential resources, characterize the radiation environment, and test new technology. To date, LRO has been operating well within the bounds of its requirements and has been collecting excellent science data images taken from the LRO Camera Narrow Angle Camera of the Apollo landing sites appeared on cable news networks. A significant amount of information on LRO s science instruments is provided at the LRO mission webpage. LRO s Guidance, Navigation and Control (GN&C) subsystem is made up of an onboard attitude control system (ACS) and a hardware suite of sensors and actuators. The LRO onboard ACS is a collection of algorithms based on high level and derived requirements, and reflect the science and operational events throughout the mission lifetime. The primary control mode is the Observing mode, which maintains the lunar pointing orientation and any offset pointing from this baseline. It is within this mode that all science instrument calibrations, slews and science data is collected. Because of a high accuracy requirement for knowledge and pointing, the Observing mode makes use of star tracker (ST) measurement data to determine an instantaneous attitude pointing. But even the star trackers alone do not meet the tight requirements, so a six-state Kalman Filter is employed to improve the noisy measurement data. The Observing mode obtains its rate information from an inertial reference unit (IRU) and in the event of an IRU failure, the rate data is be derived from the star tracker, but with degraded pointing performance. The Delta-V control mode responsibility is to maintain attitude pointing during the cruise trajectory, insertion burns and lunar orbit maintenance by adjustments made to the spacecraft s velocity magnitude and vector direction. The ACS also provides for a thruster based system momentum management algorithm (known as Delta-H) to maintain the system and wheel momentum to within acceptable levels. In the event an anomaly causes the LRO spacecraft to lose the ability to maintain its current attitude pointing, a Sun Safe mode is included in the ACS for the purpose of providing a known power and thermally safe coarse inertial sun attitude for an indefinite period of time, within the manageable limits of the reaction wheels. The Sun Safe mode is also the initial spacecraft control mode off of the launch vehicle and provides for a means to null tip-off rates immediately after separation. The nominal configuration is to use the IRU for rate information in the controller. In the event of a gyro failure a gyroless control mode was developed that computes rate information from the CSS data.
We examined the ability for pilots to estimate traffic location in an Integrated Hazard Display, and how such estimations should be measured. Twelve pilots viewed static images of traffic scenarios and then estimated the outside world locations of queried traffic represented in one of three display types (2D coplanar, 3D exocentric, and split-screen) and in one of four conditions (display present/blank crossed with outside world present/blank). Overall, the 2D coplanar display best supported both vertical (compared to 3D) and lateral (compared to split-screen) traffic position estimation performance. Costs of the 3D display were associated with perceptual ambiguity. Costs of the split screen display were inferred to result from inappropriate attention allocation. Furthermore, although pilots were faster in estimating traffic locations when relying on memory, accuracy was greatest when the display was available.