Relative Terrain Imaging Navigation for the Asteroid Redirect Robotic Mission (ARRM)
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guidance↗
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Passive navigation using image irradiance tracking
Rotorcraft operating at low altitudes require navigational schemes for detecting terrain and obstacles. Due to the nature of the missions to be accomplished and available power onboard, a passive navigation scheme is desirable in this situation. The development of a passive navigation scheme using optical image sequences and vehicle motion variables from an onboard inertial navigation scheme is described. This approach combines the geometric properties of perspective projection and a feedback irradiance tracking scheme at each pixel in the image to determine the range to various objects within the field-of-view. Derivation of the numerical algorithm and simulation results are given. Due to the feedback nature of the implementation, the computational scheme is robust. Other applications of the proposed approach include navigation for autonomous planetary rovers and telerobots.
Menon, P. K. A.↗
The McIDAS system
The man-computer interactive data access system (McIDAS) hardware and software design is outlined, with emphasis on meteorological applications. The McIDAS system features a flexible digital image enhancement device. Theory of operation, the McIDAS language, the McIDAS executive monitor, image acquisition, image parameters, image display, graphics, image navigation, and image massaging are explained. The WINDCO/CLDHGT system, developed to align time sequences of geosynchronous satellite pictures and to determine the motion and height of selected cloud targets, is also described.
Smith, E. A.↗
Passive navigation using image irradiance tracking
Rotorcraft operating at low altitudes require navigational schemes for locating the terrain and obstacles. Due to the covert nature of missions to be accomplished, a passive navigation scheme is desirable. This paper describes the development of a passive navigation scheme combining image sequences from a vehicle mounted camera with vehicle motion variables. Geometric properties of perspective projection together with an image irradiance tracking scheme at each pixel are used to determine the range to various objects within the field-of-view. Derivation of the numerical algorithm and simulation results are given. Other applications of the proposed approach include navigation for autonomous planetary rovers and telerobots.
Menon, P. K. A.↗
COxSwAIN: Compressive Sensing for Advanced Imaging and Navigation
The COxSwAIN project focuses on building an image and video compression scheme that can be implemented in a small or low-power satellite. To do this, we used Compressive Sensing, where the compression is performed by matrix multiplications on the satellite and reconstructed on the ground. Our paper explains our methodology and demonstrates the results of the scheme, being able to achieve high quality image compression that is robust to noise and corruption.
Kurwitz, Richard↗
Kalman filter based range estimation for autonomous navigation using imaging sensors
Rotorcraft operating in high-threat environments fly close to the surface of the earth to utilize surrounding terrain, vegetation, or man-made objects to minimize the risk of being detected by the enemy. Two basic requirements for obstacle avoidance are detection and range estimation of the object from the current rotorcraft position. There are many approaches to the estimation of range using a sequence of images. The approach used in this analysis differes from previous methods in two significant ways: an attempt is not made to estimate the rotorcraft's motion from the images; and the interest lies in recursive algorithms. The rotorcraft parameters are assumed to be computed using an onboard inertial navigation system. Given a sequence of images, using image-object differential equations, a Kalman filter (Sridhar and Phatak, 1988) can be used to estimate both the relative coordinates and the earth coordinates of the objects on the ground. The Kalman filter can also be used in a predictive mode to track features in the images, leading to a significant reduction of search effort in the feature extraction step of the algorithm. The purpose is to summarize early results obtained in extending the Kalman filter for use with actual image sequences. The experience gained from the application of this algorithm to real images is very valuable and is a necessary step before proceeding to the estimation of range during low-altitude curvilinear flight. A simple recursive method is presented to estimate range to objects using a sequence of images. The method produces good range estimates using real images in a laboratory set up and needs to be evaluated further using several different image sequences to test its robustness. The feature generation part of the algorithm requires further refinement on the strategies to limit the number of features (Sridhar and Phatak, 1989). The extension of the work reported here to curvilinear flight may require the use of the extended Kalman filter.
Sridhar, Banavar↗
Analysis of image-based navigation system for rotorcraft low-altitude flight
Some of the issues in the location of objects using a sequence of images from a passive sensor are examined. Image-object differential equations for a rotorcraft executing an arbitrary maneuver are developed. Assuming an onboard inertial navigation system for rotorcraft, state estimation, this study considers how object location is affected by the choice of Kalman filter estimation technique, the rotorcraft, and the object. Simulation results are presented.
Sridhar, Banavar↗
Camera Calibration and Alignment Metrology at Johnson Space Center’s Electro-Optics Laboratory
It is increasingly common to see spacecraft equipped with cameras for the purpose of navigation. Images are either sent to Earth or processed autonomously on-board to provide information about the vehicle’s position, velocity, and/or attitude. These can be images of stars or celestial bodies for absolute navigation, or images of another spacecraft for relative navigation. While monocular cameras do not provide range information, the images they capture can be processed to determine bearing vectors to target objects within the camera’s field of view. For a camera to be effective in navigation, it must be carefully calibrated and aligned. This involves accurately modeling the optical effects that govern the projection of line-of-sight directions onto the camera’s pixels and determining the camera’s orientation relative to the spacecraft’s reference frame. Engineers at Johnson Space Center’s Electro-Optics Lab regularly perform camera inspection, calibration, and alignment metrology. This was done for the Orion Optical Navigation (OpNav) Camera, the Orion Docking Camera (DCAM), and for numerous cameras belonging to commercial partners. The nature of optical navigation means that cameras must be well-calibrated and their attitude well understood to provide high accuracy bearing measurements to the navigation filter. The stringent accuracy requirements for Orion could not have been met using traditional checkerboard camera calibration or by simply relying on design drawings. This paper details the hardware, software, techniques, and algorithms used by the EOL team to achieve this level of accuracy.
Paul D Mckee↗
Camera Calibration and Alignment Metrology at Johnson Space Center’s Electro-Optics Laboratory
It is increasingly common to see spacecraft equipped with cameras for the purpose of navigation. Images are either sent to Earth or processed autonomously on-board to provide information about the vehicle’s position, velocity, and/or attitude. These can be images of stars or celestial bodies for absolute navigation, or images of another spacecraft for relative navigation. While monocular cameras do not provide range information, the images they capture can be processed to determine bearing vectors to target objects within the camera’s field of view. For a camera to be effective in navigation, it must be carefully calibrated and aligned. This involves accurately modeling the optical effects that govern the projection of line-of-sight directions onto the camera’s pixels and determining the camera’s orientation relative to the spacecraft’s reference frame. Engineers at Johnson Space Center’s Electro-Optics Lab regularly perform camera inspection, calibration, and alignment metrology. This was done for the Orion Optical Navigation (OpNav) Camera, the Orion Docking Camera (DCAM), and for numerous cameras belonging to commercial partners. The nature of optical navigation means that cameras must be well-calibrated and their attitude well understood to provide high accuracy bearing measurements to the navigation filter. The stringent accuracy requirements for Orion could not have been met using traditional checkerboard camera calibration or by simply relying on design drawings. This paper details the hardware, software, techniques, and algorithms used by the EOL team to achieve this level of accuracy.
Paul McKee↗
Simulation and analysis of image-based navigation system for rotorcraft low-altitude flight
The automation of helicopter NOE flight entails the modification of nominal trajectories on the basis of the detection and location of obstacles by means of onboard sensors. This process is presently studied using a sequence of images from a passive sensor mounted at the helicopter's center of gravity and oriented with the viewing axis along the rotorcraft's longitudinal body-axis. Three different Kalman filters are used to estimate the location of an object on the ground during the course of various simulated helicopter maneuvers; two of the three filters are found to yield good object location estimates.
Sridhar, Banavar↗
Kalman filter based range estimation for autonomous navigation using imaging sensors
The ability to detect and locate obstacles using on-board sensors and modify the nominal trajectory is necessary for safe landing of an autonomous lander on Mars. This paper examines some of the issues in the location of objects using a sequence of images from a passive sensor, and describes a Kalman filter approach to improve the range estimation to obstacles. The filter is also used to track features in the images leading to a significant reduction of search effort in the feature extraction step of the algorithm. The lack of suitable flight imagery data presents a problem in the verification of concepts for obstacle detection. An experiment is designed to acquire a sequence of images along with sensor motion parameters and the range estimation results using this imagery are presented.
Sridhar, B.↗
Interplanetary optical navigation using Charge Coupled Devices
Charge Coupled Devices (CCD) will be used as optical navigation image detectors in space missions planned for the 1980's. This paper presents analyses directed at assessing the performance of an imaging system employing a CCD (i.e., a solid state imager (SSI)), for a Jovian satellite tour environment. CCD operating principles are summarized and methods of calculating theoretical dynamic range presented. Methods of analyzing the SSI's ability to perform the fundamental optical navigation function of imaging a target body and one or more stars, are presented. This capability is expressed as a function of SSI optical and electronic parameters and of astrophysical parameters. The influence of these factors and pointing control errors on navigation picture budgets is analyzed. The effect of the sun's glare is analyzed from the standpoint of its reduction of SSI dynamic range and increase of navigation picture budget. Radiation effects on SSI navigation imaging performance are discussed and a method of analyzing probabilities of distinguishing real from false stars presented.
Davis, R. P.↗
Targeting an asteroid - The Galileo spacecraft's encounter with 951 Gaspra
On 1991 October 29, the Galileo spacecraft provided the first in situ observations of an asteroid. To a significant degree, the successful encounter with asteroid 951 Gaspra was made possible by the high accuracy of the ground-based Gaspra ephemeris and the refinement to this initial ephemeris provided by the use of optical navigation images taken on board the spacecraft itself. The success of these celestial navigation efforts was dramatically demonstrated when Gaspra appeared in the central frame of the large mosaic of CCD images-less than one asteroid diameter from Gaspra's expected location in the camera's field of view. The corrections to Gaspra's ground-based ephemeris, based upon the optical on-board navigation images, were less than 80 km. The ground-based observation program that went into this ephemeris development is discussed and the accuracy of the ephemeris is used to validate the assumptions that went into the error analysis studies.
Yeomans, D. K.↗
McIDAS-eXplorer: A version of McIDAS for planetary applications
McIDAS-eXplorer is a set of software tools developed for analysis of planetary data published by the Planetary Data System on CD-ROM's. It is built upon McIDAS-X, an environment which has been in use nearly two decades now for earth weather satellite data applications in research and routine operations. The environment allows convenient access, navigation, analysis, display, and animation of planetary data by utilizing the full calibration data accompanying the planetary data. Support currently exists for Voyager images of the giant planets and their satellites; Magellan radar images (F-MIDR and C-MIDR's, global map products (GxDR's), and altimetry data (ARCDR's)); Galileo SSI images of the earth, moon, and Venus; Viking Mars images and MDIM's as well as most earth based telescopic images of solar system objects (FITS). The NAIF/JPL SPICE kernels are used for image navigation when available. For data without the SPICE kernels (such as the bulk of the Voyager Jupiter and Saturn imagery and Pioneer Orbiter images of Venus), tools based on NAIF toolkit allow the user to navigate the images interactively. Multiple navigation types can be attached to a given image (e.g., for ring navigation and planet navigation in the same image). Tools are available to perform common image processing tasks such as digital filtering, cartographic mapping, map overlays, and data extraction. It is also possible to have different planetary radii for an object such as Venus which requires a different radius for the surface and for the cloud level. A graphical user interface based on Tel-Tk scripting language is provided (UNIX only at present) for using the environment and also to provide on-line help. It is possible for end users to add applications of their own to the environment at any time.
Limaye, Sanjay S.↗
GOES-16 ABI Navigation Assessment
The US Geostationary Operational Environmental Satellite – R Series (GOES-R) was launched on November 19, 2016and was designated GOES-16 upon reaching geostationary orbit ten days later. After checkout and calibration, GOES-16 was relocated to its operational location of 75.2 degrees west and officially became GOES East on December 18, 2017. The Advanced Baseline Imager (ABI) is the primary instrument on the GOES-R series for imaging Earth's surface and atmosphere to significantly improve the detection and observation of severe environmental phenomena. A team supporting the GOES-R Flight Project at NASA's Goddard Space Flight Center developed algorithms and software for independent verification of ABI Image Navigation and Registration (INR), which became known as the INR Performance Assessment Tool Set (IPATS). In this paper, we will briefly describe IPATS on top concept level, and then introduce the Landsat chips, chip registration algorithms, and how IPATS measurements are filtered. We present GOES-16 navigation (NAV) errors from flight data from January 2017 to May 2018. The results show a) IPATS characterized INR variations throughout the post-launch test phase; and b) ABI INR has improved over time as post-launch tests were performed and corrections applied. Finally, we will describe how estimated NAV errors have been used to assess and understand satellite attitude anomalies and scale errors etc. This paper shows that IPATS is an effective tool for assessing and improving GOES-16 ABI INR and is also useful for INR long-term monitoring.
GOES-R↗
On-Orbit Verification of GLM Navigation on GOES-16
The GOES-R flight project has developed the Image Navigation and Registration (INR) Performance Assessment Tool Set (IPATS) to perform independent INR evaluations of the optical instruments on the GOES-R series spacecraft. In this presentation, we document the development of navigation (NAV) evaluation capabilities within IPATS for the Geostationary Lightning Mapper (GLM). We also discuss the post-processing quality filtering developed for GLM NAV, and present example results for several GLM background image datasets. Initial results suggest that GOES-16 GLM is compliant with navigation requirements.
GLM↗
Temporal Evolution of SL-9 Impact Sites on Jupiter and Global Maps of Jupiter from Multi-Observatory Visible and Infrared Images
The objective of this research was to investigate the temporal behavior of the impact features on Jupiter created by the fragments of the Shoemaker Levy-9 comet that collided with the planet in July 1994. The primary observations used in the study were ground based images of Jupiter acquired from the Swedish Solar Vacuum Tube on the island of La Palma in the Canary Islands. The measurement of position of the impact features in images acquired immediately after the impact over a period of a few days revealed that the apparent drift rates were too high and that a repetitive pattern could be seen in the longitude position on successive rotations. This could be explained only by the fact that the measured longitudes of the impact sites were being affected by parallax due to a significant elevation of the impact debris above the nominal cloud top altitude value used for image navigation. Once the apparent positions are analyzed as a function of the meridian angle, the parallax equation can be used to infer the height of the impact features above the cloud deck, once the true impact position (longitude) for the feature is known. Due to their inherent high spatial resolution, the HST measurements of the impact site locations have been accepted widely. However, these suffer from the parallax themselves since few of them were obtained at central meridian. Ground based imaging have the potential to improve this knowledge as they do observe most of the impact sites on either side of the central meridian, except for the degraded resolution. Measurements over a large number of images enables us to minimize the position error through regression and thus estimate both the actual impact site location devoid of parallax bias, and also of the altitude level of the impact debris above the cloud deck. With rapid imaging there is the potential to examine the time evolution of the altitude level. Several hundred ground based images were processed, navigated and subjected to the impact site location measurements. HST images were also acquired and used to calibrate the results and to improve the sample. The resources available enabled an in-depth study only of impact site A, however, many more images have since become available through the global network observations through Lowell Observatory.
Limaye, Sanjay S.↗
On-Orbit Verification of GLM Navigation on GOES-16
The GOES-R flight project has developed the Image Navigation and Registration (INR) Performance Assessment Tool Set (IPATS) to perform independent INR evaluations of the optical instruments on the GOES-R series spacecraft. In this paper, we document the development of navigation (NAV) evaluation capabilities within IPATS for the Geostationary Lightning Mapper (GLM). We also discuss the post-processing quality filtering developed for GLM NAV, and present example results for several GLM datasets. Initial results suggest that GOES-16 GLM is compliant with navigation requirements.
On-Orbit↗