2
Methods for Characterization

Information about the orbital debris environment is needed to determine the current and future hazard to space operations from debris. Unfortunately, the debris environment is difficult to characterize accurately. Only the largest debris objects can be repeatedly tracked by ground-based sensors; detection and tracking of the numerous smaller pieces of debris is much more difficult. A variety of measurement techniques have been developed, however, that enable statistical estimates to be made of the number and characteristics of some size ranges of smaller debris items in some orbits. These estimates rely on scientific and engineering models of population characteristics. More complex models are used to estimate the characteristics of the future debris population.

TRACKING AND CATALOGING ORBITAL DEBRIS

Current Capabilities

A small percentage of debris in orbit is tracked and cataloged. The orbital parameters (e.g., period, inclination, apogee, and perigee) of these objects are entered into a catalog, generally along with information on the object's origin—only objects with known origins are entered into the catalog—and its radar or optical cross section. These data can then be used for such purposes as predicting potential collisions and recognizing space object breakups. Cataloging space objects requires an expensive network of sensors capable of observing objects periodically to determine any changes in their orbital elements and of continually performing orbit determination computations.



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2 Methods for Characterization Information about the orbital debris environment is needed to determine the current and future hazard to space operations from debris. Unfortunately, the debris environment is difficult to characterize accurately. Only the largest debris objects can be repeatedly tracked by ground-based sensors; detection and tracking of the numerous smaller pieces of debris is much more difficult. A variety of measurement techniques have been developed, however, that enable statistical estimates to be made of the number and characteristics of some size ranges of smaller debris items in some orbits. These estimates rely on scientific and engineering models of population characteristics. More complex models are used to estimate the characteristics of the future debris population. TRACKING AND CATALOGING ORBITAL DEBRIS Current Capabilities A small percentage of debris in orbit is tracked and cataloged. The orbital parameters (e.g., period, inclination, apogee, and perigee) of these objects are entered into a catalog, generally along with information on the object's origin—only objects with known origins are entered into the catalog—and its radar or optical cross section. These data can then be used for such purposes as predicting potential collisions and recognizing space object breakups. Cataloging space objects requires an expensive network of sensors capable of observing objects periodically to determine any changes in their orbital elements and of continually performing orbit determination computations.

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Currently, only two systems in the world have the necessary network of ground-based sensors and computational capability to carry out this task. One, the Space Surveillance Network (SSN), is operated by the United States under the control of the U.S. Space Command; the other, the Space Surveillance System (SSS), is operated by the Russian military (see Box 2-1). The primary purpose of each system is to detect objects that present a military threat; thus, although each is capable of detecting certain types of debris, neither system is optimized to perform the task of maintaining a debris catalog. BOX 2-1 The Russian and U.S. Space Surveillance Systems Figure 2-1 displays the location of the sensors of the Russian and U.S. space surveillance systems. The Russian Space Surveillance System (SSS) has a primary data acquisition system that includes 10 radars (operating in either UHF [ultrahigh frequency], VHF [very high frequency], or C-band) and 12 optical and electro-optical facilities. The radars are used to track objects in lower orbits; the optical and electro-optical facilities are used only for tracking objects in high orbits. Additional sensors may be used occasionally for important tasks and experiments. The lack of a worldwide network of sensors results in some major breaks in observation and some zones in which space objects cannot be observed. Data from the sensors (approximately 50,000 measurements per day) are transmitted to the Russian Space Surveillance Center, where they are processed, and the space object catalog is updated and replenished. The Russian Space Surveillance Center also identifies detected objects, updates space object orbital elements and calculates orbital elements sets for new observations, plans future observations, determines orbital lifetimes, and provides information to other space programs (Batyr et al., 1993; Batyr et al., 1994). The U.S. Space Surveillance Network (SSN) consists of more than 20 radar and optical sensors, most of which are not dedicated to space surveillance and are tasked on an ''as-needed" basis. In general, radars are used to track objects in low-altitude orbits and optical sensors are used for high-altitude detection; some radars, however, are deep-space sensors capable of detecting objects in GEO. Although many of the SSN's sensors are located within the continental U.S., others are spread out longitudinally. Data from the network are fed to the U.S. Space Control Center, which processes the data and maintains a catalog of space objects. Orbital element sets are transmitted back to the sensors to allow them to continue tracking detected objects and are also made available to selected satellite operators and space system users. The Space Control Center also processes space object breakup data and performs collision warning for some space activities, such as launches and U.S. Space Shuttle operations in orbit.

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FIGURE 2-1 Sensors of the SSS and SSN. SOURCE: Kaman Sciences Corporation.

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The ease with which a particular space object can be tracked depends on its optical or radar cross section (RCS) as well as its orbital parameters. In general, objects with larger optical or RCSs are more easily detectable than objects with smaller cross sections. Both the optical and the radar cross sections of particular space objects can vary greatly—which is not surprising for a collection of irregular-shaped objects. Uncertainty in the relation of RCS to actual size means that the smallest objects that these systems are able to catalog is uncertain, but since few objects in the SSS or SSN catalogs have an RCS of less than about 0.01 square meter, the commonly reported minimum trackable size has been 10 cm in diameter. Recent radar range calibration of fragments produced in the laboratory, combined with measurements by short-wavelength radar and by ground telescopes (Henize and Stanley, 1990), have provided additional insight into the limiting size of the objects maintained in the catalog. These data indicate that for LEO orbital inclinations above about 30 degrees, the U.S. catalog contains some objects as small as 10 cm but is not complete at this size range. The catalog for LEO objects with inclinations greater than 30 degrees, however, is estimated to be 90 to 99 percent complete for objects larger than 20 cm. As orbital altitude increases, the minimum size of debris that can be detected by ground-based sensors increases. However, this does not mean that the minimum-sized object that can be cataloged increases steadily with altitude. The opportunity for repeated observations and the predictability of an object's position in orbit also increase with altitude, making the maintenance of the orbital elements of a high-altitude detected object easier. Consequently, for altitudes below about 2,000 km, there is no simple statement of the limiting size of the catalog, other than that it is in the 10- to 30-cm range. However, radar detection sensitivity rapidly decreases with increasing altitude, and by 5,000 km the smallest BOX 2-2Comparison of the SSN and SSS Catalogs The U.S. and Russian space object catalogs are in general agreement for LEO objects greater than 50 cm in diameter. For space objects with diameters between 10 and 50 cm, the U.S. catalog is more complete. Above LEO, both catalogs generally maintain the orbital elements only of spacecraft and rocket bodies greater than 1 meter in diameter. Due to the lack of a worldwide network of sensors, the Russian space object catalog does not include objects in a significant portion of GEO and can only periodically track objects in highly eccentric, low-inclination orbits.

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objects detectable by radar are about 1 meter in diameter. Above 5,000 km, optical telescopes become the primary sensors; these have the sensitivity to track meter-sized objects in GEO—though this does not mean that all meter-sized objects in GEO are cataloged. Current space surveillance systems have difficulties in cataloging some space objects in highly elliptical orbits and low-inclination orbits. Objects in highly elliptical orbits are difficult to detect because they spend a large fraction of their time at very high altitudes, while objects in low-inclination orbits are more difficult to detect because of the relative lack of sensors (in either network) at low latitudes. Recent experiments by the U.S. Space Command confirmed the SSN's difficulty in cataloging space objects in low-inclination and high-eccentricity orbits (Pearce et al., in press; Clark and Pearce, 1993). It should be emphasized that these peculiarities do not represent deficiencies in the way the networks perform their normal mission of maintaining a catalog for military reasons, but rather reflect the fact that they were not designed to characterize the space debris population. Improving Tracking and Cataloging Capabilities International cooperation might present an opportunity to make some improvement in the catalogs without significant expenditure. The SSS and the SSN both routinely track objects not found in the other's catalog, so sharing catalog data will improve the completeness of both catalogs. (It is not at all clear, however, that sharing catalog data would increase the accuracy with which the orbital parameters of cataloged objects are known.) Since both the SSS and the SSN have similar limitations, it is already clear that information sharing between the two systems would not significantly increase the size of the catalog or improve detection of medium-sized debris. There is also a potential obstacle to such collaboration in that there are legitimate security reasons for not sharing all data received from national surveillance networks; this may not be a major issue because both networks are capable of editing data before sharing them. One factor that limits the ability of most space surveillance sensors to detect smaller debris is that they were not designed to detect small objects. Most space surveillance radars operate in the UHF and VHF ranges; debris smaller than about 10 cm in diameter are in the Rayleigh scattering region for these frequencies and are thus not easily detected, and the record of their orbital elements is not easily kept current. A National Aeronautics and Space Administration (NASA) study on the possible protection of the Space Station against debris concluded that 10 cm was an inherent limit for the current sensors of the SSN and that these sensors

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could not easily be modified to improve sensitivity (NASA, 1990). The Russian SSS is currently working to increase its capability to observe small objects with existing sensors, focusing research on lowering the sensitivity thresholds of its current radars and on developing new methods to acquire weak signals using narrow-angle and narrow-beam sensors and making full use of existing data regarding the space object's motion. While this research may allow the SSS to track somewhat smaller debris, radars operating at much shorter wavelengths (e.g., 3 cm wavelength to detect 1 cm diameter objects in LEO) will ultimately be required to detect debris significantly smaller than 10 cm in diameter. Increasing the accuracy of predictions of the future location of objects in LEO is another means of improving tracking and cataloging capabilities. Such improvement is a necessary requirement for the development of an effective collision warning capability in LEO; increased accuracy is required to keep the number of false alarms for such a system low, since moving spacecraft is a task not undertaken lightly. (Collision warning schemes are discussed in some detail in Chapter 7.) Currently, uncertainty in the future location of objects due to atmospheric drag is the major limitation on catalog accuracy in LEO. This unavoidable uncertainty is due to variability in the density of the upper atmosphere and uncertainty about objects' orbital attitude (and thus the cross-sectional area they present to the atmosphere) and normally dwarfs inaccuracies caused by observation errors and errors in propagation theory. As is shown in Figure 2-2, atmospheric drag retardation along the orbital track of medium to large space objects in 300- to 600-km-altitude orbits can range up to hundreds of kilometers per day. The most optimistic estimate of the accuracy with which atmospheric drag can be determined is ±15 percent; consequently a prediction error (which cannot be calibrated) of several kilometers per day is typically accumulated. Keeping the number of false alarms for a LEO collision warning system at a tolerable level thus requires frequent reobservations of debris objects. (Collision warning systems for objects in regions where atmospheric drag is less critical would not have this limitation; in GEO, for example, errors in estimates of objects' initial positions would be responsible for the majority of false alarms.) Improvements in propagation accuracy could be achieved by positioning sensors to minimize the required propagation time and by improving understanding of upper-atmospheric density fluctuations. Improving the ability to track and catalog objects in orbits above LEO is basically a matter of improving the sensors (both radar and optical) used to detect high-altitude objects and acquiring enough data from these sensors to determine the orbital parameters of the objects they detect. Detecting objects that are less bright (because they either are smaller,

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FIGURE 2-2 One day along-track drag retardation for a random sample of cataloged objects at 300–600 km. SOURCE: U.S. Naval Space Command Satellite Catalog. are further away, or have a lower albedo) might be accomplished with either larger-aperture telescopes or telescopes equipped with charge-coupled devices (CCDs). Siting debris-detecting sensors at low latitudes could allow a broad variety of objects, including those in low-inclination orbits, to be detected. Finally, increasing the number of sensors available to detect debris would allow for better tracking of cataloged objects and for more searches for uncataloged objects. BOX 2-3 Detecting Debris with CCDs Charge-coupled devices can be used in optical sensors to convert incoming light directly to electric charges; the magnitude of the output signal is proportional to the light intensity. CCDs have not yet outperformed conventional sensors for detection of objects in LEO because the rapid movement of LEO objects requires that the signal be integrated, which in turn requires an assumption of direction of motion, severely limiting the detection rate. CCDs are improving, however, and are already outperforming non-CCD sensors for observation of high-altitude debris (which does not move as rapidly across the field of view). Upgrading the SSN's GEODSS (ground-based electro-optical deep-space sensors) to use CCDs has been considered.

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SAMPLING ORBITAL DEBRIS Since it is currently impossible to track all debris in orbit, measuring and characterizing the uncataloged debris population must be carried out by sampling the debris flux at particular locations and times and using the data as a basis for estimating the characteristics of the general population. The orbital debris flux can be sampled either directly (with spacecraft surfaces that are later returned to Earth for examination) or remotely (using ground- or space-based radars or optical telescopes that record debris as it passes through their fields of view). Although sampling—combined with predictive models—can be used to provide important clues to the nature of debris populations that are not included in the catalog, it is important that the limitations of the technique, including any sampling biases, be taken into account. For example, rather than portraying the steady-state small debris population in LEO, in situ measurements of small debris particles acquired by examining returned spacecraft surfaces portray only the average debris flux along a particular orbit during a particular time frame. Remote Sampling from Earth Optical Sensors At first glance, the use of ground-based telescopes to sample the debris population seems like a promising technique. Such sampling is usually carried out by pointing the telescope in a fixed direction and counting objects as they pass through its field of view. A 1-meter diameter telescope in darkness can theoretically detect a sunlit metal sphere 1 cm in diameter at 900-km distance. If this were all there was to the problem, data from optical sensors could be used to estimate the population of objects larger than 1 cm in diameter in orbits up to 900 km. Unfortunately, most debris fragments reflect much less light than a metal sphere; typically only about 10 percent of the light is reflected. In addition, objects in LEO have angular velocities of at least 0.5 degree per second when viewed from the ground, which further increases the difficulty of optical detection. Finally, there can be difficulty in discriminating between debris and the luminosity caused by meteors interacting with the atmosphere. Theoretically, this last problem can be solved completely by using two telescopes and determining the object's altitude with the measured parallax, or solved partially by using the object's angular velocity to approximate its altitude. Despite these drawbacks, ground-based telescopes engaged in sampling have provided some valuable information on the LEO population of debris around 10 cm in diameter. Tests to detect uncataloged debris in

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LEO with ground-based telescopes have been carried out by NASA (in cooperation with the Massachusetts Institute of Technology's Lincoln Laboratory and the U.S. Space Command) since 1983. These tests used electro-optical telescopes of approximately one 1-m diameter and, as mentioned earlier, aided in the determination of the approximate size ranges of debris contained in the SSN catalog. Although the exact size of debris detectable by these telescopes is not certain since they measure pieces of debris with a variety of unknown reflectivities, the average minimum object size detectable is slightly smaller than 10 cm (Kessler, 1993). Ground-based telescopes also can be used to sample the space debris population above LEO. The limited efforts to sample the HEO population to date include surveys of GEO by the Russian Academy of Sciences and NASA, and surveys of GTO performed by ground-based electro-optical deep-space sensors sites. Tests to observe objects in the geostationary orbit with ground-based optical sensors have detected uncataloged objects, but there have been no comprehensive surveys of the geostationary ring and the size of its uncataloged population remains unclear. Many of the features suggested earlier for improving the tracking and cataloging of high-altitude debris using optical sensors (e.g., larger apertures, low-inclination sites, or the use of CCDs) would also be useful for sampling the debris population. One additional feature particularly useful for sampling is a wide field of view, which gives an optical sensor the ability to sample large areas and thus gather more data. This is very useful in optical sensing, where the need for good lighting conditions can severely limit the hours a telescope can be used to look for objects in Earth orbit. NASA is beginning to use a 3-m diameter "liquid-mirror" telescope to sample the debris population. Large liquid mirrors can be constructed relatively inexpensively because they use mercury, spun to keep it in the necessary parabolic shape, to form their reflecting surface. Such telescopes are constrained to always point vertically; although this makes some types of observation difficult, it does not hamper debris sampling. NASA finished construction of its first liquid mirror, which will operate within the United States, in 1994 and has already obtained stellar images from the telescope's temporary site in Houston. A second liquid-mirror telescope to be sited near the equator is planned. These telescopes should be able to regularly detect debris down to about 2-cm diameter at altitudes up to 500 km. Radar Sampling Short-wavelength ground-based radars also have been used effectively to sample the medium-sized debris population in LEO. Radars

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sample debris in a "beam park" mode (similar to the sampling technique used by ground telescopes), in which the radar stares in a fixed direction (preferably vertically to maximize sensitivity) and debris is counted as it passes through the radar's field of view. Since 1987, significant amounts of sampling data have been obtained by using the Arecibo, Goldstone, and Haystack radars. In addition, the longer-wavelength FGAN and MU radars have demonstrated the ability to sample the medium and large debris population, respectively (Mehrholz, 1993; Sato et al., 1992). In 1989, the Arecibo Observatory's high-power 10-cm-wavelength radar and the Goldstone Deep Space Communications Complex's 3-cm-wavelength radar were used (with the assistance of other radars) to obtain orbital debris data. Neither radar was designed to track debris, but both were expected to detect small debris if it existed. In 18 hours of operation, the Arecibo experiment detected nearly 100 objects larger than an estimated 0.5 cm in diameter (Thompson et al., 1992). In 48 hours of observation, the Goldstone radar detected about 150 objects larger than approximately 0.2 cm in diameter (Goldstein and Randolph, 1990). Because little effort was made either to accurately define the collection area of these radars or to properly calibrate them, these data have fairly large uncertainties. Even so, these experiments demonstrated that data could be obtained in a beam park mode and that there was a large population of smaller debris to be detected. Since 1990, more than 2,400 hours of data have been collected and analyzed from the Haystack radar (Stansbery et al., 1994). This 3-cm-wavelength radar situated at 42°N latitude can be pointed either vertically or south, 10 or 20 degrees above the horizon. In the vertical mode, maximum sensitivity is obtained, but detection in LEO is limited to orbits with inclinations greater than 42 degrees. When the radar is pointed south, sensitivity is poorer, but LEO objects with inclinations as low as 25 degrees can be detected. The complete data set from the Haystack observations contains information on the size, altitude, range rate (the rate of change in the distance from the object to the radar), and direction of motion of debris at altitudes up to 1,500 km. The data on the direction of motion can be used to determine an object's orbital inclination with a typical uncertainty of about 5 degrees (though uncertainty can be much higher for objects that are barely detectable). The range rate data can be used to determine orbital eccentricity when pointed vertically and inclination when pointed near the horizon. In the vertically pointing mode, the smallest objects detected range from about 0.3 cm at 350 km to 0.7 cm at 1,400 km. In the south-pointing mode the smallest objects detectable are larger—typically about 1 cm. Haystack transmits right circularly polarized radio waves and receives both left and right circularly polarized

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waves. The polarization of the reflection can be used to infer the general shape of the objects detected. Calibration of the data acquired by using sampling radars can be achieved by a number of techniques. These include radar range measurements of fragments of known size, shape, and mass, and the use of orbital calibration spheres. The Haystack radar used both of these techniques. In this case, the range measurements indicated that irregular fragments reflected similarly to spheres but a broad distribution of possible signal returns must be considered in interpreting the data. Existing calibration spheres, as well as the Orbital Debris Radar Calibration Spheres (ODERACS), were also used in calibration. Future efforts to sample the debris population with ground-based radars may be the most effective means to collect data on medium-sized debris in LEO. Improvements in this capability can be achieved by (1) performing more debris sampling with existing radars; (2) siting new radars so they can detect low-inclination debris populations; and (3) using high-powered, short-wavelength radars to detect smaller debris. Increasing the amount of time that radars spend sampling debris is basically a problem of allocating the resources needed to carry out additional searches. Continued sampling efforts with existing radars can increase statistical confidence in existing data and, over time, could provide information on changes in the debris population. However, the Haystack, Goldstone, and Arecibo radars, which were not designed to detect debris, have other users preventing them from being used full-time for debris detection and are expensive to operate. For these reasons, the Haystack Auxiliary Radar (HAX) was recently built specifically to detect debris. HAX, which is located near the Haystack radar, will not be as sensitive as Haystack, but its slightly larger field of view and lower BOX 2-4 The ODERACS Experiment The ODERACS experiment was launched from the U.S. Space Shuttle in March of 1994 and provided calibration for a number of Earth-based radar and optical sensors. In this experiment, six aluminum spheres (two 5 cm in diameter, two 10 cm in diameter, and two 15 cm in diameter) were released into LEO. One sphere of each type had a polished surface whereas the other had a rough surface. This experiment demonstrated the validity of sampling debris with a radar and helped calibrate both radar and optical sensors. A similar future experiment will release three spheres and three dipoles to further calibrate the sensors. The dipoles are intended to calibrate polarization measurements, which are important for determining debris shape.

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impact crater on a spacecraft surface is related not only to the impacting object's mass but also to its velocity (speed and direction), which is related to the object's orbital characteristics. Population characterization models can thus be employed to predict a probability distribution of velocities from an assumed orbit distribution, which can then be used to create a probability distribution of particle masses. The impacting object's mass can then be estimated from this probability distribution. A similar method can be used to estimate the size of space objects detected by a telescope. For a telescope, the brightness of an observed object is a function of the object's size, optical properties, and orientation as it passes through the telescope's field of view. In this case, population characterization models can use expected distributions of optical properties and orientations to convert the measured distributions of brightnesses into a distribution of probable sizes. NASA's "Engineering Orbital Debris Model" (Kessler et al., 1991), and the ESA engineering model (Sdunnus and Klinkrad, 1993) are examples of a particular type of population characterization model used by spacecraft design engineers. These models predict the flux of orbital debris that might strike a spacecraft during its lifetime as a function of debris size and velocity for various spacecraft orbital altitudes and inclinations. Although such models are based primarily on measurements of the orbital debris environment, they use the results of more complex models to extrapolate these measurements. This type of model also serves as a "reference model" and is used to compare measurements and evaluate relative hazards. There are currently no recognized standard population characterization reference models; researchers and designers must rely on models that have not undergone peer review or that may not contain the latest data. This can potentially lead experimenters to interpret their data improperly or spacecraft designers to improperly assess the hazard to their spacecraft. Models of the Future Debris Population The earliest models used to predict the future orbital debris environment (Kessler and Cour-Palais, 1978; Kessler, 1981b; Su and Kessler, 1985) built on the population characterization models and combined breakup models with atmospheric drag models to predict the environment in the 1980s and beyond. These relatively simple models predicted an environment in the 1990s that is not greatly different from that being measured today. Currently, more complex models are used to predict the growth in the orbital debris population. Such models combine a traffic model, a breakup model, and an orbit propagation model to predict possible future orbital debris population states. Two such models in common use

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today are NASA's EVOLVE (Reynolds, 1993) and the University of Braunschweig's CHAIn (Rex and Eichler, 1993). These models take estimates of the current space object population, and new debris from various sources (e.g., collisions, explosions, mission-related debris), and propagate the orbits of these objects over time to create a static description of the debris population at a selected time in the future. (The predictions these models make about the future debris environment are discussed at length in Chapter 8.) Each of the component models that goes into such models as EVOLVE and CHAIN has its own characteristics and uncertainties. A traffic model keeps track of spacecraft, rocket bodies, and any associated debris launched into orbit by recording when these objects are placed in orbit, their sizes and masses, and their initial orbital elements. Some of these objects will break up into smaller fragments or degrade and release smaller debris. A breakup model describes the number of fragments generated in a breakup, as well as the changes in velocity that place them into slightly different orbits. An orbit propagation model then determines how the orbits of both intact space objects and space object fragments change as a function of time. Traffic Modeling The growth and evolution of the Earth-orbiting space object population will be influenced in large measure by the frequency and character of future space operations. Space traffic models, coupled with propagation and breakup models, predict the magnitude and nature of these operations and their effect on the LEO and HEO space object populations. Traffic models must account for (1) all objects (e.g., spacecraft, rocket bodies, mission-related debris) to be placed into Earth orbit; (2) the apogee, perigee, and inclination of each object's orbit; (3) the size and mass of each object, (4) any planned reorbiting or deorbiting maneuvers at the end of an object's functional lifetime; and (5) any stored energy left in the rocket body or spacecraft that may cause it to explode. Ideally, space traffic models should look far enough into the future to assess the impact of actions to curb the growth of the total space object population. Predicting even the overall level of space activities over such a time frame, however, is often futile, since very few national or commercial space programs have credible long-range plans extending for more than 8 to 10 years, and even these plans are affected by programmatic, technical, and economic trends; changing national and market requirements; and advances in technology. As a further complication of the problem, it is important to know the population in each orbital region, so that low traffic estimates in one altitude region of the model do not offset

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unanticipated missions in another altitude region. For all of these reasons, space traffic models have historically been poor predictors of future activities. Nevertheless, scenarios of potential levels of future activity can be developed and used to evaluate the influence of future launch activity on population. Breakup Models Breakup models are used to characterize the fragments generated in space object breakups. The results of these models are typically used to estimate existing debris populations and to predict the future population. Most breakup models use the type and amount of energy causing the breakup of a space object of a given mass to estimate the resulting fragment distribution. The most useful breakup models are semiempirical and incorporate the laws of physics as well as existing data on breakups in their calculations. However, there are two major difficulties involved in developing an accurate breakup model. First, no ''typical" amount of debris is generated in an explosion or collision, since there are many different causes of explosions and many different types of collisions (e.g., two spacecraft colliding head-on will produce more debris than a collision between a 10-cm fragment and a spacecraft's solar array). Second, and perhaps more problematically, there are very few data on which to base breakup models. Few experiments have been conducted to improve breakup models; most available data have been obtained as a byproduct of experiments with other objectives. Explosion data have been gathered from such sources as an accidental Atlas missile explosion, munition explosion tests (Bess, 1975), and explosions in orbit, although recently, some groundbased explosion tests have been conducted specifically to determine the velocity and mass distributions of explosion fragments (Fucke, 1993). Data on collisions are also limited; for many years, the primary sources of such data were the pioneering work of Bess at the NASA Langley Research Center in 1975 and several series of tests performed for the U.S. military during the late 1970s and early 1980s. Debris from the military tests were examined for NASA in the 1980s explicitly to refine the foundation of satellite impact breakup models. The deliberate on-orbit collisions of P-78 and D-180 in the mid 1980s added to this database, though no significant data are available on the smaller (untrackable) fragments produced in these tests. Recently, however, more complete data on the fragments created in a collision-induced breakup were acquired from tests specifically designed to improve breakup models. In these tests, the U.S. Defense Nuclear Agency shot a 150-gram projectile at 6 km/s into parts of an actual space

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BOX 2-6 Modeling Debris Clouds One specialized type of breakup model focuses on the dynamics of the debris clouds formed following a collision or explosion in orbit (Chobotov, 1990). Although these models do not contribute significantly either to estimates of the current population or to the understanding of the long-term debris population, they can be useful in predicting the short-term hazard to spacecraft in orbits near where a breakup occurred. Such information is particularly useful for designers of spacecraft constellations, who are interested in ensuring that the breakup of one spacecraft will not overly endanger other spacecraft in the constellation. craft and into a full-scale spacecraft model (Hogg et al., 1993). Unfortunately, analysis of the data from these tests was not completed due to a lack of funding. Consequently they have not resulted in any significant improvements in most breakup models, although the tests did demonstrate that breakup models that predicted few small fragments were incorrect. NASA has recently contracted with Kaman Sciences Corporation to complete the analysis of these tests. These data, particularly the data from the in-orbit breakups, shed light mostly on the characteristics of the larger debris produced. Only the largest fragments of a breakup in orbit can be tracked, although fairly accurate velocity and area-to-mass ratios can be determined for these fragments. Even in ground tests, often only the larger fragments are recovered, since a great amount of work is required to recover the smaller pieces. As a result, the amount and the velocities of smaller debris produced in breakups are not well known. Propagation Models Orbit propagation models predict how the orbits of space objects change as a function of time. This information is used for two major purposes: determining the location of particular space objects in the relatively near term (typically over a period of a few days or less for purposes of collision avoidance or reentry predictions) and making long-term (typically over a period of years) predictions about the debris environment. The short- and long-term propagation tasks have some common characteristics, but each also faces unique challenges. Both short- and long-term propagation models must take into account the various forces acting on space objects in Earth orbit. As described in Chapter 1, these include atmospheric drag, solar radiation pressure, gravitational perturbations by the Sun and Moon, and irregularities

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in the gravitational field of the Earth. Fortunately, few objects in Earth orbit are affected significantly by many of these forces; the particular forces relevant to each object depend on the object's orbit and area-to-mass ratio. Since accurate orbit propagation models that include all forces acting on an orbiting object can be very computation intensive, most models take into account only the forces that most strongly affect the space objects in a particular orbital region. (For example, in LEO, where orbital inclination does not change significantly with time, the long-term propagation task is reduced to determining the changes in orbital perigee and apogee due to atmospheric drag.) Accurate short-term deterministic propagation models require that the forces on an object be known and predictable. The inherent unpredictability in atmospheric drag (discussed in Chapter 1) thus introduces error into the predictions of short-term deterministic propagation models for objects in low LEO orbits (less than about 500 km). Accurate deterministic predictions in this region for tasks such as collision warning, which require a high degree of accuracy and propagation of at least a significant fraction of a day, can be achieved only by making repeated observations with increasing calculation fidelity as the time to impact decreases. The Russian SSS uses such an approach to solve actual tasks in debris-related contingencies (e.g., space objects about to reenter). Its approach employs short-term density prediction models utilizing (in addition to knowledge of solar and geomagnetic activity) data on the current drag experienced by other space objects to specify atmospheric density. Uncertainty in the day-to-day atmospheric drag is not such a problem for long-term propagation modeling in LEO, both because much of the uncertainty can be averaged over time and because long-term models are not as concerned with objects in the orbits most affected by atmospheric drag (which tend to reenter the atmosphere fairly rapidly). The long-term uncertainty in atmospheric drag, however, still limits the fidelity of long-term propagation models in LEO. If solar and geomagnetic activity are known, long-term atmospheric density models are accurate to within about 20%. However, atmospheric density can vary by more than a factor of 10 over the 11-year solar cycle, and the level of future solar cycles is unpredictable. Consequently, only very simple LEO propagation models are normally justified for long-term space object population studies. Although atmospheric drag ceases to be a factor above LEO, space objects at higher altitudes are influenced by solar radiation pressure, lunar and solar perturbations, and irregularities in the Earth's gravity. These can affect an orbit's inclination and eccentricity as well as its apogee and perigee altitude, so more complex propagation models are re-

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quired to obtain predictive accuracy. Although such models exist and are capable of providing sufficient accuracy for long-term modeling, they require a very large amount of computation. New hardware, however, is making the calculation-intensive computations much more feasible. It is not yet clear what approximations could be made to enable the creation of accurate long-term HEO propagation models that do not require a large computational capability. Short-term propagation modeling (for purposes of collision avoidance, etc.) at high altitudes is difficult because of the problems inherent in tracking objects at such distances. One problem is that only very large objects at those distances from the Earth can be detected by current space surveillance sensors. Another is the fairly large uncertainty in the exact position of detected objects. Although short-term predictions have been made for GEO since the 1970s, and avoidance maneuvers have even been carried out based on this information, the uncertainty in the exact position of GEO objects means that the number of false alarms was probably high. FINDINGS Finding 1: The U.S. and Russian space surveillance networks are able to detect objects down to a size of about 10 cm in LEO. Increasing fractions of larger objects are tracked so that the LEO debris environment in the size range greater than 20 cm is adequately characterized by the catalogs. However, both catalogs underrepresent objects in highly elliptical orbits, low-inclination orbits, and high-altitude circular orbits. As the orbital altitude increases, the minimum size of objects cataloged grows, until at GEO not even all objects with a diameter greater than 1 meter are tracked. Finding 2: A number of approaches could be used to improve on current space object catalogs. Sharing catalog data between nations would improve our understanding of the magnitude and distribution of the population of large space objects. A network of new short-wavelength radars would be required to catalog LEO debris significantly smaller than that currently being tracked. Catalogs of large objects in regions above LEO, where data are particularly sparse, could be improved with increased use of large-aperture or CCD-equipped optical sensors. Further analysis is needed to determine whether sharing data from national space object catalogs would result in an improved combined catalog. Finding 3: In situ direct sampling techniques can detect particle sizes up to about 1 mm in LEO, but the population of medium-sized debris is sufficiently sparse that very large collection areas would be required to

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obtain a statistically meaningful sample. Ground-based remote sampling has been, and will remain for some time, the most effective means of measuring debris in the medium size ranges. Finding 4: There has been no systematic approach to sampling space for orbital debris; most sampling to date has been performed when the opportunity arose, resulting in a series of investigations that studied a limited region of space over a limited amount of time. There is a need for national or international strategies to help prioritize detector development, deployment, data collection, and analysis of historical and new data. Such strategies are necessary to gain a better understanding of the sources of small and medium debris and the variations in these populations with respect to altitude, inclination, and time. Finding 5: Population characterization models can be used by spacecraft designers to estimate the debris hazard to their spacecraft. Debris researchers can use them to integrate available data and to provide a framework for predicting the results of future measurements. As new data become available, existing models should be revised to produce a comprehensive, standard, peer-reviewed reference model. Finding 6: Models predicting the future space object population in Earth orbit draw on traffic, breakup, and orbit propagation models. These component models have large inherent uncertainties; as a result, many characteristics of the future debris population cannot be predicted with precision. Experience to date with such models has, however, been fairly positive; relatively simple models from the late 1970s and early 1980s predicted an environment in the 1990s that is not greatly different from that being measured today. REFRENCES Atkinson, D.R., J.D. Mulholland, A.J. Watts, S.L. Lapin, and J.D. Wagner. 1993. Meteoroid and Debris Monitoring: An Industry Summary. Contract Final Report. Contract Number 959626. Pasadena, California: NASA Jet Propulsion Laboratory. Batyr, G., S. Veniaminov, V. Dicky, V. Yurasov, A. Menshicov, and Z. Khutorovsky. 1993. The current state of the Russian Space Surveillance System and its capability in surveying space debris. Pp. 43-47 in Proceedings of the First European Conference on Space Debris, Darmstadt, Germany, 5–7 April 1993. Darmstadt: European Space Operations Center. Batyr, G., S. Veniaminov, V. Dicky, S. Kravchenco, and V. Yurasov. 1994. Some Preliminary Results of ODERACS Experiment. Paper presented at U.S./Russia Orbit Determination and Prediction Workshop, Washington, D.C. Bendisch, J., J.P. Hoffmann, R. Liebscher, and F. Rollenhagen. 1993. Detection of space debris by the use of space-based optical sensors. Pp. 91–97 in Proceedings of the First European Conference on Space Debris, Darmstadt, Germany, 5–7 April 1993. Darmstadt: European Space Operations Center.

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Bess, T. D. 1975. Mass Distribution of Orbiting Man-Made Space Debris. NASA TN D-8108. Washington, D.C.: National Aeronautics and Space Administration. Chobotov, V. 1990. Dynamics of orbital debris clouds and the resulting collision hazard to spacecraft. Journal of the British Interplanetary Society 43:187–195 . Clark, J., and E. Pearce. 1993. Briefing presented for the National Aeronautics and Space Administration/Department of Defense Orbital Debris Workshop, Colorado Springs, Colorado, September 1–3. de Jonge, A.R.W., 1993. IR detection of space debris. Briefing presented to the National Research Council Committee on Space Debris Workshop, Irvine, California, November 18. Fucke, W. 1993. Fragmentation experiments for the evaluation of the small size debris population. Pp. 275–280 in Proceedings of the First European Conference on Space Debris, Darmstadt, Germany, 5–7 April 1993. Darmstadt: European Space Operations Center. Goldstein, R., and L. Randolph. 1990. Rings of Earth Detected by Orbital Debris Radar. JPL Progress Report 42–101, May 15. Pasadena, California: NASA Jet Propulsion Laboratory. Henize, H., and J. Stanley. 1990. Optical observations of orbital debris. AIAA-90-1340. AIAA/NASA/DoD Orbital Debris Conference, Baltimore, Maryland, April 16–19. Washington D.C.: American Institute of Aeronautics and Astronautics. Hogg, D.M., T.M. Cunningham, and W.M. Isbell. 1993. Final Report on the SOCIT Series of Hypervelocity Impact Tests. Wright Laboratory-TR-93-7025. Dayton, Ohio: Wright Laboratory. Hüdepohl, A., H. Iglseder, and E. Grün. 1992. Analysis of the Results of Two-Year Operations of the Munich Dust Counter—A Cosmic Dust Experiment on Board the Satellite HITEN. International Astronautical Federation paper 92-0561. Paris: International Astronautical Federation. Kassel, P.C., and J.J. Wortman. 1994. Metal-oxide-silicon capacitor detectors for measuring micrometeoroid and space debris flux. Paper submitted to the AIAA Journal of Spacecraft and Rockets. Kessler, D.J. 1981a. Derivation of the collision probability between orbiting objects: The lifetime of Jupiter's outer moons. Icarus 48:39–48 . Kessler, D.J. 1981b. Sources of orbital debris and the projected environment for future spacecraft. Journal of Spacecraft and Rockets 18(4):357–360 . Kessler, D.J. 1993. Orbital debris environment. Pp. 251–262 in Proceedings of the First European Conference on Space Debris, Darmstadt, Germany, 5–7 April 1993. Darmstadt: European Space Operations Center. Kessler, D.J., and B.G. Cour-Palais. 1978. Collision frequency of artificial satellite: The creation of a debris belt. Journal of Geophysical Research 83(A6):2637–2646 . Kessler, D.J., R.C. Reynolds, and P.D. Anz-Meador. 1991. Space Station Program Natural Environment Definition for Design. NASA SSP 30425, Revision A. Houston, Texas: NASA Johnson Space Center. Kinard, W.H. 1993. Description of the orbital meteoroid and debris counting experiment to fly on the CLEMENTINE inter-stage adapter spacecraft. P. 148 in NASA Conference Publication 10120, Third LDEF Post-Retrieval Symposium Abstracts. Hampton, Virginia: NASA Langley Research Center. Kuzin, G.A. 1993. Meteorite and Man-Made Microparticle Impact Detection Methodology and Equipment on the Space Stations "SALYUT" and "MIR." Briefing presented to the National Research Council Committee on Space Debris Workshop, Irvine, California, November 18. McDonnell, J.A.M., and K. Sullivan. 1992. Hypervelocity impacts on space detectors: Decoding the projectile parameters. Hypervelocity Impacts in Space, 39. Canterbury, United Kingdom: University of Kent at Canterbury Unit for Space Sciences. Mehrholz, D. 1993. Potentials and limits of space object observations and data analysis

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