Near-Earth Asteroid Rendezvous Mission NEAR Imaging Team Member Proposal

M. Malin, Malin Space Science Systems, Inc.

Table of Contents


Participation as a Facility Team Member of the Multispectral Imaging System (MIS) Facility Instrument Team on the Near Earth Asteroid Rendezvous (NEAR) mission is proposed. The investigation proposes to acquire and analyze images of the asteroid 433 Eros (an S-type asteroid), using the MIS Facility Instrument, in order to address problems associated with the geological and geophysical evolution of Eros, and related to questions concerning the nature and evolution of other small bodies in the solar system. These objectives will be met through observations of surface features during the approximately one year duration of the NEAR mission.

Research goals of this proposal include studies of the shape (large-scale relief and morphology) of Eros, of the general geology and geomorphology of the asteroid, and of small-scale morphology as determined by visual inspection of images and extraction of relief information using computer techniques. Degradation of relief and aggradation of impact ejecta and the nature of surface and near-surface transport of debris will be investigated, in an attempt to better understand the development of regolith on small bodies and its influence on the preserved cratering record. Structural features (grooves, ridges, etc.) will also be examined, and interpreted in concert with other Project Science Group members in terms of the internal configuration of the asteroid.

The proposed participation as a Team Member of the MIS Team (MIST) would include involvement in instrument design review, and in the development and implementation of instrument calibration requirements, in keeping with the investigator's present and past experience as Principal Investigator on the Mars Observer/Mars Global Surveyor Cameras and as a Team Member on the Comet Rendezvous/Asteroid Flyby (CRAF) Imaging Science Sub-System Team. Of specific focus during the instrument development phase of the project will be effective geometric, photometric, and spatial response calibration. Participation in mission design and planning is also anticipated, with the objective of defining operational procedures and techniques consistent with the low-cost, high-science return objectives of the operations phase of the mission. For the most part, existing hardware and software will be used and/or modified to address the operational and scientific objectives of this investigation; work will be conducted at both the Applied Physics Laboratory's observational control center and at the investigator's home institution.

During mission operations, the investigation will focus observations on preliminary body shape and the rotation axis and rate (Approach and 1000 km Orbit Phases), refined body properties and local geology (early Nominal Orbit Phase), and detailed topography and geomorphology (Nominal Orbit Phase). Using existing software, first-order processing of NEAR MIS images will be quite rapid--without relying of any special computer capabilities, the entire data set can be reprocessed from raw data in about three days. Other programs (existing and to be modified from extant software) will permit rapid development of shape and relief models. Archiving will occur as agreed upon by the PSG and Project.

The scope of the 6 year effort includes approximately 12.5 months of senior research personnel, about 20 months of research support personnel, and 18.4 months of administrative support. A phased approach will be implemented, with the investigator spending about 12 weeks on the project during the first year (for participation in instrument calibration and testing), about 6 weeks the second year (to participate in spacecraft/payload testing), and only about 2 weeks each year during the cruise to Eros. The investigator will devote approximately 40% of his time to the project during mission operations. Support personnel will devote about 1.5 person years to the project during the 18 month operations and data archiving period.

Investigation and Technical Plan

Investigation Description and Background

Objectives and Significance

This investigation has two general scientific objectives: to determine the size, shape, and spin state of the Near-Earth asteroid 433 Eros, and to characterize the geology and morphology of the surface, with particular emphasis on the development and transport of fine debris. To accomplish these objectives, a third, technical objective of the investigation is to insure that the geometric, photometric, and spatial response performance of the primary instrument of interest, the Multispectral Imaging System (MIS), is well understood and documented.

The specific investigations to be conducted during the mission operations phase of the mission include the following:

1. Locate the spin axis position, orientation, and determine the spin rate;

2. Establish the shape of Eros using images systematically acquired during the Approach and 1000 km Orbit phases of the mission;

3. Enhance the shape model using images systematically acquired from the Nominal Rendezvous Orbit;

4. Track features between spacecraft maneuvers (optical navigation) as a secondary means of orbit determination to probe the mass and mass distribution of the asteroid;

5. Map geologic and geomorphic features to provide context to compositional mapping; and

6. Study slopes and surface morphology for clues to debris generation (by cratering and other possible processes) and its movement across the surface.

These objectives are directly related to three of the four the primary mission science objectives as noted on Pg. 3 of the Announcement of Opportunity:

Investigation Approach

Investigation Concept

The concept for this investigation is relatively simple: images of a small body (433 Eros) can be used to derive bulk shape properties, and combined with mass determinations derived from spacecraft tracking, then used to calculate the gross density of the asteroid. Higher resolution topography and tracking measurements, made closer to the asteroid, permit more detailed comparisons from place to place on the asteroid.

Geological studies of planetary surfaces proceed by the evaluation of classical photointerpretative criteria: planimetric configuration, topographic relief, albedo, color, texture, pattern, and association. Judicious application of prior experience (e.g., studies of Phobos, Deimos, Gaspra, and Ida) and, with caution, terrestrial analogies (e.g., formation of grooves by piping), permits the interpretation to be extended to process, material, and time relationships. Geomorphic maps illustrate the configuration of a surface and illuminate the specific processes that have acted on the surface. Geologic maps synthesize geomorphic, compositional, and stratigraphic information into an interpretative framework.

In the specific study of morphology as related to the development and evolution of the surficial debris layer, images of craters, lineaments, grooves, ridges, and other landforms are acquired, and subsequently examined, at a resolution that permits the scale of their development and potential variations to be characterized. Many of these features show pronounced differences if expressed in dense, hard rock or granular material. The search for these differences, and the scale at which they occur, is paramount to studies of asteroidal regoliths. For example, evidence suggests that these debris layers are thicker than would be expected from ballistic redistribution of impact crater ejecta, leading to the speculation that the near-surface asteroidal material is incompetent. Impact craters also provide information on timescales, although uncertainties in impacting body size/frequency distribution, impact velocity, and impactor composition often reduce this utility.

An important aspect of this investigation is the acquisition of calibration information. Both basic information (e.g., effective focal length, field distortion, etc.) and derived information (e.g., signal-to-noise ratio, absolute photometric response, etc.) are needed if the reduced spacecraft data are to have the desired accuracy and precision. Some of these measurements are relatively easy to perform; others require substantial effort (e.g., targets in sub-system thermal/vacuum testing). With the collection of data of the appropriate type, quality, and quantity, analysis and derivation of the desired factors is generally simple.

Collaborative studies will also be important to this investigation. It is anticipated that, owing to the small size of the total Facility Science Team, each Team Member will have primary responsibility for some area, and will collaborate with other team members in other areas. This investigator plans to work closely with those studying the photometric and multispectral attributes of the surface using the MIS, with investigators studying mineralogical composition using the Near-Infrared Spectrometer (NIS), and with the radio science and LIDAR investigators studying the bulk properties of the asteroid.

Investigation Methods and Procedures

Shape and Relief Determinations

A variety of techniques exist for determining the shape of an irregular body. These include several types of photogrammetry, photoclinometry, limb reconstructions, and fused techniques (those that incorporate one or more of the other approaches). In addition, at least some of these techniques can be employed in either fully manual or fully automated modes, and in modes that are partially automated or partially manual. In this section, Viking observations of Phobos are used to illustrate some of these techniques.

Limb Curves

Limb curves (and their close relatives, terminator lines) provide significant, though not necessarily complete, information about the shape of a body. With sufficient axial sampling, most of the features of the body can be reconstructed (the principal limitation being that the interiors of concave features such as craters never appear on the limb). Limb curve reconstruction may suffer from operational limitations if it is not possible to obtain a sufficient number of equally spaced, high resolution views around known, multiple axes, to eliminate all possible ambiguity (i.e., in cases where only one axis of rotation can be used, a small hill located between two larger hills might never appear on the limb).


Figure 1: Manual Definition of Limb and Terminator Shape

Figure 1 shows a technique for manual definition of limb and terminator positions in multiple images. The technique permits fitting an initial figure (generally a triaxial ellipsoid) to the object as observed in several images, and then deforming that figure by incorporation of features of known geometry (such as craters with circular planform and parabolic cross-section) or by manually moving grid points to specific locations. The particular software shown in Figure 1 can be used without prior information on pointing and other relevant information or, more effectively, used with the Navigation Ancillary Information Facility (NAIF) toolkit and SPICE (Spacecraft-Planet-Instrument-"Camera"-Event) navigation/attitude kernels for precise manipulation. In this latter case, limb/terminator fitting and other forms of photogrammetry become quite similar. Using this software, a dozen images can be fit in a few hours.


In control point methods, features common to multiple images are identified and their coordinates on the image plane of each image measured. These measurements have traditionally have been performed manually, although automated systems, based on pattern matching, have been developed over the past 5-8 years. A least-squares procedure is then applied to the ensemble of measurements, along with information about the target/spacecraft position and camera orientation. Some or all of the information can be held fixed if it is known with adequate precision; with a sufficient number of control points, all of the parameters can be left to be adjusted by the procedure. The result is an estimate of the position in three-space of each control point, and updated values of the camera orientation and spacecraft position.

To produce a surface from the scattered points, an interpolation procedure must be used. A variety of spline-based and minimum-energy surface fitting routines have been implemented in existing software. As might be expected, some routines work well under some circumstances, while performing poorly in others. Also as might be expected, the quality of the surface is generally dependent on the number of points, as is the time needed for processing.

Stereophotogrammetric techniques are, as a class, a special case of the more general control point methodology. In stereoscopy, the position and orientation of the camera is generally known, a limited number of images (often two) are used to find feature correspondences, and there is usually considerable overlap of features. One strength of stereo is that autocorrelation or other automated image-matching techniques can be used to build a much larger number of corresponding points than would typically be determined for control points. Using the camera coordinates, feature displacement owing to parallax maps directly to surface relief.

Figure 2 shows the "front end" of a set of programs used in stereogrammetry. Left and right images (in side-by-side format or portrayed as anaglyphs) are examined stereoscopically, and a movable cursor used to establish points "on" the virtual surface. Points are manually selected individually. This tool can be used to quickly generate topographic profiles (as shown in Figure 2), but its primary use is to edit points generated automatically by a combined edge/area correlation program.


Figure 2: Point Registration for Stereogrammetric Analysis

The point positions, derived either manually or automatically, are usually expressed as heights above a nominal ground plane, and a surface is interpolated by the methods mentioned above to produce a height grid or digital terrain model.


Photoclinometry, also known as shape-from-shading, attempts to invert the orientation of the surface at each pixel by using a shading model and knowledge of the illumination conditions. Traditional applications of this technique in planetary science have used line-based, integrative methods, which are highly sensitive to errors caused by mismatches between the shading model and the actual surface, imperfections in the imaging system, and albedo variations. At least some of these limitations can be overcome by the use of area-based techniques developed over the past fifteen years by the computer vision community. These techniques attempt to distribute error across the image by globally minimizing criteria like departure from integrability. Although the line-based methods usually require manual input, the area-based techniques are typically fully-automated (the implementation used to create the relief shown in Figure 3 was fully automated). Once the orientation of each surface patch is known, a height map can be built up by simple integration or more sophisticated iterative methods.


Figure 3: Visualization of Photoclinometrically-derived Relief

Figure 3 shows the results of applying a photoclinometry program to a portion of the Viking image of Phobos. It does not show the original data produced by the program, in which the shape of Phobos dominated the relief (as can be seen in the profile in Figure 2). In the upper left corner is a high-pass filtered version of the photoclinometry, where filtering was used as a surrogate for a shape model. The original image is shown at the same scale in the bottom center, and an oblique view of the image superimposed on the relief (with a vertical exaggeration of 4X) is seen in the upper right. Such illustrations are useful in visualizing spatial and topographic relationships, but quantitative values are more important in estimating volumes, relief, and potential energy.

Combining methods

The methods described above occupy different positions within a two-dimensional design space where one axis is the volume of information produced and the other is the accuracy of that information. Along the volume axis, photoclinometry produces a dense distribution of surface information, potentially determining the location of every imaged point on the body, while point photogrammetry only locates as many points as can be found to correspond on multiple images. One limb curve produces a distribution dense only in the plane perpendicular to the viewing direction (and even that is compromised by occultation effects); multiple limb curves are sparse about the axes of rotation, and interpolation is still required to construct a complete surface.

On the other axis, point photogrammetry is the most accurate and well-characterized method. Photoclinometry is easily confused by albedo characteristics, and is subject to a variety of pathological cases that can result in poor surface reconstruction, especially on a global scale. Typically, the error propagation characteristics of photoclinometry algorithms lead to good local results -- small features are well-reconstructed -- but error buildup leads to large global errors. Operational limitations in image coverage may cause limb-based methods to miss features or not recognize discontinuities.

The fact that these techniques have different strengths and weaknesses suggests that the best approach is to combine the results from all of them -- an approach called "sensor fusion" by the computer vision community. A coarse surface approximation will be derived from control points supplemented with a finer model supplied by manually-edited automated limb- and terminator-matching. A technique much like surface rendering of Computer-Aided Tomography (CAT) scans will be used to synthesize many limb models into a single model. This model will be compared with photometric models of comparable resolution, and the process iterated. High spatial resolution photometrically derived relief will be extracted after the shape models converge, with local constraints provided by high resolution stereogrammetry.

Instrument Calibration Requirements

Important Assembly/Component Measurements

The following basic measurements should be made at the assembly level [Note: items marked with asterisks (*) should be checked for dependences on spectral filter)]:




Instrument (Subsystem) Calibration

Photometric Calibration

All photometric measurements should be performed for all eight filters and at a variety of gain/offset/exposure values.

Exposure time

Establish actual exposure time control. If physically shuttered, establish in environmental thermal/vacuum (T/V) testing exposure time control as function of temperature.

Relative gain/offset

Establish how electronic gain and offset controls the final output DN level.

Absolute flux response

Establish how final output DN level is related to incident energy on each detector. May use calibrated photodiode or empirically-measured photon transfer curve and measurement of the instrument's ability to convert photons to electrons.

Flat field

Use to measure variations in response between individual elements of the detector, and across the detector, so these effects can be removed from images.

Noise performance

Measure the signal-to-noise performance of the system at various operational values. Both actual and susceptibility to random and patterned noise should be measured. Dark current and flat field images should be acquired at room temperature and at operating temperature in T/V testing.

Photometric stability with time

Measurements should be made of specific attributes that might provide insight into the photometric stability of the system. Stability over time (i.e., does it produce the same DN values for the same illumination measured at different times?) is required for photometric use. Two subgoals should be addressed: measurement of stability during turn-on transients, and over significant timescales (hours to days).

Photometric stability over temperature

Measurements should be made of the stability of the system over temperature (i.e., does it produce the same DN values for the same illumination at different temperatures?)


Stray light

The stray light properties of the instrument should be measured (e.g., how much background signal will be produced by off-axis light from Eros?). This can have a significant impact on photometric performance.

Spatial mapping function

The angular and spatial position of specific points on the detector and through the optics must be measured accurately in order to perform geodesy, photogrammetry, and optical navigation.

Modulation Transfer Function (MTF) and Point Spread Function (PSF)

The PSF and MTF are measures of the instrument's ability to discriminate small features, and its value is critical to the success of this investigation. Two aspects of the instrument should be examined: the MTF/PSF performance in the line and sample directions must be measured separately (since the detector sampling is not square, see Figure 4), and the sensitivity of these functions (in both directions) should be measured as a function of temperature. It would be useful to determine the performance of the instrument with both real, two-dimensional image data and with point sources. The Project should consider in-flight, post-launch star imaging prior to conducting the approach phase optical navigation, as PSF performance may influence the ability of the MIS to detect Eros as it is approaching.


Figure 4: Illustration of Effect of Asymmetric Pixel Size


Knowledge of instrument alignment, relative to the spacecraft coordinate system and in particular with respect to the spacecraft attitude as determined by the attitude control and knowledge subsystem and included in instrument telemetry, is required for determining the position of a target from one or more images (photogrammetry). Targeting (i.e., determining when and/or where an image should be taken, and how the spacecraft must be oriented to permit that observation) also requires knowledge of instrument alignment.

Instrument to instrument boresights

Should be measured to permit coordinated observations and analyses. The FOV of the NIS should be known to 0.05°. The requirement for the LIDAR is TBD.


Power draw

Should be measured under bench and operating environmental conditions, for all operating modes. This will permit intelligent power management during periods of time when spacecraft power is at a premium.

Engineering telemetry sensors

Functions to convert raw telemetry counts to engineering units (temperatures, currents, and voltages) are needed so that instrument health can be monitored during T/V testing and flight.

Environment behavior

Photometric/stability and optical/MTF/PSF performance should be measured under operational environmental conditions.

Ground Operations Support

No special ground operations support requirements have been identified at this time. After review of relevant Project documents and discussions with MOS and GDS personnel, some potential requirements may be identified. These will be discussed with the MIS Team Leader and, if appropriate, brought to the Project for consideration.

Flight Operations Support

Mission and operations planning software and communications will be critical to the success of the NEAR mission. Both manual and automated sequence generation should be supported. Interactive as well as batch processing may be needed. These types of planning tools are available to the investigator, and will be modified as appropriate to support his investigation. He expects to work closely with the MOS and GDS developers in determining what other software exists or will exist at the time of this mission, and what interaction would be most beneficial to the Project.

Data Reduction and Analysis

Data Processing (Reduction)

Upon receipt of raw instrument data, initial "quick-look" processing will be performed. This processing will include: random noise removal (despiking), first-order photometric calibration (pre-launch filter factors, exposure compensation, flat field, blemish removal), camera distortion removal (spatial resampling convolved with MTF restoration), and 12-to-8 bit rescaling (for display purposes). Cosmetic processing (contrast enhancement) may also be applied. Second-order processing might include application of in-flight radiometric calibration data during the photometric calibration step (after random noise removal) and additional spatial filtering and contrast enhancement. First-order processing takes approximately 4 seconds per frame on a single-processor SPARCStation 10 using existing software (80 frames can be processed in about 5 minutes, for a processing throughput of about 400 kbps); thus, first order processing can be accomplished and delivered on a daily basis.

Data Analysis

Data analysis techniques (as described above) to be applied to the images includes procedures to extract the rotation axis and rate, measure the three-dimensional figure, and produce high-resolution relief information. Once shape information is available, processing will involve photometric function removal and photoclinometric production of topography. Processing associated with extraction of high resolution topography is considerably more time consuming--combined stereogrammetric and photoclinometric processing of a relief model of a 412 X 537 pixel area takes about 3 hours on a single-processor SPARCStation 10. Mosaics and other reduced forms of data will be assembled for analysis, and measurements made on both volatile and hardcopy versions (depending on the scale and area covered). Much of the morphologic and geologic analysis is subjective, using photointerpretative skills.

Data Archiving

The investigator proposes to participate with the MIS Team Leader in maintaining the "best version" data base. The mission total data volume, calculated on the basis of information provided on Pg. 29-31 of the Announcement of Opportunity (~152 days at 2000 bps and ~213 at 6000 bps), is roughly 140 Gb. The MIS will probably account for about 70% of these data (96 Gb) Given the relatively fast processing applied to these data (400 kbps), the entire data set could be reprocessed from raw data in less than 3 days on one single-processor SPARCstation 10. Thus, "maintenance" may entail replacing all previous versions with newer versions at specific times, or piece-wise "besting" of the data.

The proposer will work closely with the Team Leader and other members of the PSG to define useful data formats for the storage and exchange of data between investigations, and will make both original and modified data files available to other investigators on mutually agreed upon bases.

The volume of data to be returned by NEAR will fill approximately 230 CD-ROMs. About 160 of these will be needed to contain the raw MIS data. Additional ancillary data will probably fill an additional 10-20 CDs. Production of two to three disks a week is a relatively simple task, and one that can be highly automated. The investigator will work closely with the PSG and the NEAR Project, in particular with engineers with the GDS, in defining this process.

Appendix A: Biographical Information

Principal Investigator: Michael C. Malin


A. B., 1971, University of California, Berkeley, Physics; Dissertation, 1975, Ph.D., 1976, California Institute of Technology, Planetary Sciences and Geology.


President and Chief Scientist, Malin Space Science Systems, Inc., 1990-present; Research Professor, 1990-1991, Professor, 1987-1990, Associate Professor, 1982-1987, Assistant Professor, 1979-1982, Department of Geology, Arizona State University; Member of the Technical Staff, Earth and Planetary Sciences Section, Jet Propulsion Laboratory, 1975-1979.

Spaceflight Hardware Experience:

Principal Investigator, NASA Mars Global Surveyor Orbiter Camera Flight Experiment, 1994-present. Principal Investigator, NASA Mars Observer Camera Flight Experiment, 1986-1994. Principal Investigator, Planetary Instrument Definition and Development Program - Small Spacecraft Imaging Systems, 1990-present. Co-Investigator, NASA Mars Observer/Mars Global Surveyor Thermal Emission Spectrometer. Team Member, NASA Comet Rendezvous Asteroid Flyby Imaging Science Team, 1986-1992.

Science Experience:

Guest Investigator, Magellan Venus Radar Investigation Group, 1990-present. Participating Scientist, Mars '94 Mission, 1990-present. Principal Investigator, Venus Data Analysis Program, 1993-present. Principal Investigator, NASA Planetary Geology and Geophysics Program, 1975-1993. Principal Investigator, NSF Polar Programs (U.S. Antarctic Research Program), 1982-1987, 1993-present. Principal Investigator, NSF Earth Sciences, 1983-1987.

Research Interests:

NASA research includes photogeological studies of Viking Orbiter and Lander (Mars), Voyager (satellites of Jupiter and Saturn), and Pioneer Venus (Venus) images, and terrestrial field studies of eolian, fluvial, volcanic, and mass movement phenomena (conducted in Iceland, Alaska, Hawaii, Washington, and Utah). NSF research includes studies of cold–environment weathering and erosion phenomena in Antarctica and evaluation of explosive volcanic eruption processes through the use of computer graphic techniques.


Malin received a five year MacArthur Fellowship in 1987.

Recent Publications:

Malin, M. C., 1992, Mass movements on Venus: Preliminary results from Magellan Cycle I observations, J. Geophys. Res. 97 (E10), 16337-16352.

Malin, M. C., Danielson, G. E., Ingersoll, A. P., Masursky, H., Veverka, J., Ravine, M. A., and Soulanille, T. A., 1992, The Mars Observer Camera, J. Geophys. Res. 97(E5) 7699-7718.

Malin, M. C., Danielson, G. E., Ravine, M. A., and Soulanille, T. A., 1991, Design and Development of the Mars Observer Camera, Int. J. Imaging Sys. Tech. 3, 76-91.

Phillips, R. J., Grimm, R. E., and Malin, M. C., 1991, Hot-spot evolution and the global tectonics of Venus, Science 252, 651-658.

McEwen, A. S. and Malin, M. C., 1989, Dynamics of sediment gravity flows: Lahars, avalanche, pyroclastic flows, and blast surge of Mount St. Helens, J. Volcan. Geotherm. Res. 37, 205-231.

Kelley, A. D., Malin, M. C., and Nielson, G. M., 1988, Terrain simulation using a model of stream erosion: Computer Graphics 22(4), 263-268.

Malin, M., 1986, Rates of geomorphic modification in ice-free areas, southern Victoria Land, Antarctica: Antarctic Journal of the United States 20(5), p. 18-21.

Malin, M. C., 1986, Density of martian north polar layered deposits: Implications for composition: Geophys. Res. Lett. 13 (5), p. 444-447.

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