Orbital Debris Research at NASA

The United States has one of the most active programs of research of the orbital debris environment in the world. Much of the research is conducted by NASA s Orbital Debris Program Office at the Johnson Space Center. Past work by NASA has led to the development of national space policy which seeks to limit the growth of the debris population and limit the risk to spacecraft and humans in space and on the Earth from debris. NASA has also been instrumental in developing consistent international policies and standards. Much of NASA's efforts have been to measure and characterize the orbital debris population. The U.S. Department of Defense tracks and catalogs spacecraft and large debris with it's Space Surveillance Network while NASA concentrates on research on smaller debris. In low Earth orbit, NASA has utilized short wavelength radars such as Haystack, HAX, and Goldstone to statistically characterize the population in number, size, altitude, and inclination. For higher orbits, optical telescopes have been used. Much effort has gone into the understanding and removal of observational biases from both types of measurements. NASA is also striving to understand the material composition and shape characteristics of debris to assess these effects on the risk to operational spacecraft. All of these measurements along with data from ground tests provide the basis for near- and long-term modeling of the environment. NASA also develops tools used by spacecraft builders and operators to evaluate spacecraft and mission designs to assess compliance with debris standards and policies which limit the growth of the debris environment

Radar Cross Section of Orbital Debris Objects

This discussion is concerned with the radar-data analysis and usage involved in the building of model orbital debris (OD) populations in the near-Earth environment, focusing on radar cross section (RCS). While varying with radar wavelength, physical dimension, material composition, overall shape and structure, the RCS of an irregular object is also strongly dependent on its spatial orientation. The historical records of observed RCSs for cataloged OD objects in the Space Surveillance Network are usually distributed over an RCS range, forming respective characteristic patterns. The National Aeronautics and Space Administration (NASA) Size Estimation Model provides an empirical probability-density function of RCS as a function of effective diameter (or characteristic length), which makes it feasible to predict possible RCS distributions for a given model OD population and to link data with model from a statistical perspective. The discussion also includes application of the widely used method of moments (MoM) and the Generalized Multi-particle Mie-solution (GMM) in the prediction of the RCS of arbitrarily shaped objects. Theoretical calculation results for an aluminum cube are compared with corresponding experimental measurements

Growth in the Number of SSN Tracked Orbital Objects

The number of objects in earth orbit tracked by the US Space Surveillance Network (SSN) has experienced unprecedented growth since March, 2003. Approximately 2000 orbiting objects have been added to the "Analyst list" of tracked objects. This growth is primarily due to the resumption of full power/full time operation of the AN/FPS-108 Cobra Dane radar located on Shemya Island, AK. Cobra Dane is an L-band (23-cm wavelength) phased array radar which first became operational in 1977. Cobra Dane was a "Collateral Sensor" in the SSN until 1994 when its communication link with the Space Control Center (SCC) was closed. NASA and the Air Force conducted tests in 1999 using Cobra Dane to detect and track small debris. These tests confirmed that the radar was capable of detecting and maintaining orbits on objects as small as 5-cm diameter. Subsequently, Cobra Dane was reconnected to the SSN and resumed full power/full time space surveillance operations on March 4, 2003. This paper will examine the new data and its implications to the understanding of the orbital debris environment and orbital safety

NASA Orbital Debris Program

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NASA Measurement Summary

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NASA Orbital Debris Engineering Model ORDEM2008 (Beta Version)

This is an interim document intended to accompany the beta-release of the ORDEM2008 model. As such it provides the user with a guide for its use, a list of its capabilities, a brief summary of model development, and appendices included to educate the user as to typical runtimes for different orbit configurations. More detailed documentation will be delivered with the final product. ORDEM2008 supersedes NASA's previous model - ORDEM2000. The availability of new sensor and in situ data, the re-analysis of older data, and the development of new analytical techniques, has enabled the construction of this more comprehensive and sophisticated model. Integrated with the software is an upgraded graphical user interface (GUI), which uses project-oriented organization and provides the user with graphical representations of numerous output data products. These range from the conventional average debris size vs. flux magnitude for chosen analysis orbits, to the more complex color-contoured two-dimensional (2-D) directional flux diagrams in terms of local spacecraft pitch and yaw

Orbital Debris Detection and Tracking Strategies for the NASA/AFRL Meter Class Autonomous Telescope (MCAT)

MCAT (Meter-Class Autonomous Telescope) is a 1.3m f/4 Ritchey-Chr tien on a double horseshoe equatorial mount that will be deployed in early 2011 to the western pacific island of Legan in the Kwajalein Atoll to perform orbital debris observations. MCAT will be capable of tracking earth orbital objects at all inclinations and at altitudes from 200 km to geosynchronous. MCAT s primary objective is the detection of new orbital debris in both low-inclination low-earth orbits (LEO) and at geosynchronous earth orbit (GEO). MCAT was thus designed with a fast focal ratio and a large unvignetted image circle able to accommodate a detector sized to yield a large field of view. The selected primary detector is a close-cycle cooled 4Kx4K 15um pixel CCD camera that yields a 0.9 degree diagonal field. For orbital debris detection in widely spaced angular rate regimes, the camera must offer low read-noise performance over a wide range of framing rates. MCAT s 4-port camera operates from 100 kHz to 1.5 MHz per port at 2 e- and 10 e- read noise respectively. This enables low-noise multi-second exposures for GEO observations as well as rapid (several frames per second) exposures for LEO. GEO observations will be performed using a counter-sidereal time delay integration (TDI) technique which NASA has used successfully in the past. For MCAT the GEO survey, detection, and follow-up prediction algorithms will be automated. These algorithms will be detailed herein. For LEO observations two methods will be employed. The first, Orbit Survey Mode (OSM), will scan specific orbital inclination and altitude regimes, detect new orbital debris objects against trailed background stars, and adjust the telescope track to follow the detected object. The second, Stare and Chase Mode (SCM), will perform a stare, then detect and track objects that enter the field of view which satisfy specific rate and brightness criteria. As with GEO, the LEO operational modes will be fully automated and will be described herein. The automation of photometric and astrometric processing (thus streamlining data collection for environmental modeling) will also be discussed

Characterizing the Space Debris Environment with a Variety of SSA Sensors

Damaging space debris spans a wide range of sizes and altitudes. Therefore no single method or sensor can fully characterize the space debris environment. Space debris researchers use a variety of radars and optical telescopes to characterize the space debris environment in terms of number, altitude, and inclination distributions. Some sensors, such as phased array radars, are designed to search a large volume of the sky and can be instrumental in detecting new breakups and cataloging and precise tracking of relatively large debris. For smaller debris sizes more sensitivity is needed which can be provided, in part, by large antenna gains. Larger antenna gains, however, produce smaller fields of view. Statistical measurements of the debris environment with less precise orbital parameters result. At higher altitudes, optical telescopes become the more sensitive instrument and present their own measurement difficulties. Space Situational Awareness, or SSA, is concerned with more than the number and orbits of satellites. SSA also seeks to understand such parameters as the function, shape, and composition of operational satellites. Similarly, debris researchers are seeking to characterize similar parameters for space debris to improve our knowledge of the risks debris poses to operational satellites as well as determine sources of debris for future mitigation. This paper will discuss different sensor and sensor types and the role that each plays in fully characterizing the space debris environment

Satellite Material Type and Phase Function Determination in Support of Orbital Debris Size Estimation

In performing debris surveys of deep-space orbital regions, the considerable volume of the area to be surveyed and the increased orbital altitude suggest optical telescopes as the most efficient survey instruments; but to proceed this way, methodologies for debris object size estimation using only optical tracking and photometric information are needed. Basic photometry theory indicates that size estimation should be possible if satellite albedo and shape are known. One method for estimating albedo is to try to determine the object's material type photometrically, as one can determine the albedos of common satellite materials in the laboratory. Examination of laboratory filter photometry (using Johnson BVRI filters) on a set of satellite material samples indicates that most material types can be separated at the 1-sigma level via B-R versus R-I color differences with a relatively small amount of required resampling, and objects that remain ambiguous can be resolved by B-R versus B-V color differences and solar radiation pressure differences. To estimate shape, a technique advanced by Hall et al. [1], based on phase-brightness density curves and not requiring any a priori knowledge of attitude, has been modified slightly to try to make it more resistant to the specular characteristics of different materials and to reduce the number of samples necessary to make robust shape determinations. Working from a gallery of idealized debris shapes, the modified technique identifies most shapes within this gallery correctly, also with a relatively small amount of resampling. These results are, of course, based on relatively small laboratory investigations and simulated data, and expanded laboratory experimentation and further investigation with in situ survey measurements will be required in order to assess their actual efficacy under survey conditions; but these techniques show sufficient promise to justify this next level of analysis

Phase Function Determination in Support of Orbital Debris Size Estimation

To recover the size of a space debris object from photometric measurements, it is necessary to determine its albedo and basic shape: if the albedo is known, the reflective area can be calculated; and if the shape is known, the shape and area taken together can be used to estimate a characteristic dimension. Albedo is typically determined by inferring the object s material type from filter photometry or spectroscopy and is not the subject of the present study. Object shape, on the other hand, can be revealed from a time-history of the object s brightness response. The most data-rich presentation is a continuous light-curve that records the object s brightness for an entire sensor pass, which could last for tens of minutes to several hours: from this one can see both short-term periodic behavior as well as brightness variations with phase angle. Light-curve interpretation, however, is more art than science and does not lend itself easily to automation; and the collection method, which requires single-object telescope dedication for long periods of time, is not well suited to debris survey conditions. So one is led to investigate how easily an object s brightness phase function, which can be constructed from the more survey-friendly point photometry, can be used to recover object shape. Such a recovery is usually attempted by comparing a phase-function curve constructed from an object s empirical brightness measurements to analytically-derived curves for basic shapes or shape combinations. There are two ways to accomplish this: a simple averaged brightness-versus phase curve assembled from the empirical data, or a more elaborate approach in which one is essentially calculating a brightness PDF for each phase angle bin (a technique explored in unpublished AFRL/RV research and in Ojakangas 2011); in each case the empirical curve is compared to analytical results for shapes of interest. The latter technique promises more discrimination power but requires more data; the former can be assembled in its essentials from fewer measurements but will be less definitive in its assignments. The goal of the present study is to evaluate both techniques under debris survey conditions to determine their relative performance and, additionally, to learn precisely how a survey should be conducted in order to maximize their performance. Because the distendedness of objects has more of an effect than their precise shape in calculating a characteristic dimension, one is interested in the techniques discrimination ability to distinguish between an elongated rectangular prism and a short rectangular prism or cube, or an elongated cylinder from a squat cylinder or sphere. Sensitivity studies using simulated data will be conducted to determine discrimination power for both techniques as a function of amount of data collected and range (and specific region) of phase angles sampled. Empirical GEODSS photometry data for distended objects (dead payloads with solar panels, rocket bodies) and compact objects (cubesats, calibration spheres, squat payloads) will also be used to test this discrimination ability. The result will be a recommended technique and data collection paradigm for debris surveys in order to maximize this type of discrimination