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NASA NTRS2009

Photometric Studies of GEO Debris

The photometric signature of a debris object can be useful in determining what the physical characteristics of a piece of debris are. We report on optical observations in multiple filters of debris at geosynchronous Earth orbit (GEO). Our sample is taken from GEO objects discovered in a survey with the University of Michigan's 0.6-m aperture Schmidt telescope MODEST (for Michigan Orbital DEbris Survey Telescope), and then followed up in real-time with the SMARTS (Small and Medium Aperture Research Telescope System) 0.9-m at CTIO for orbits and photometry. Our goal is to determine 6 parameter orbits and measure colors for all objects fainter than R = 15 th magnitude that are discovered in the MODEST survey. At this magnitude the distribution of observed angular rates changes significantly from that of brighter objects. There are two objectives: 1. Estimate the orbital distribution of objects selected on the basis of two observational criteria: brightness (magnitude) and angular rates. 2. Obtain magnitudes and colors in standard astronomical filters (BVRI) for comparison with reflectance spectra of likely spacecraft materials. What is the faint debris likely to be? In this paper we report on the photometric results. For a sample of 50 objects, more than 90 calibrated sequences of R-B-V-I-R magnitudes have been obtained with the CTIO 0.9-m. For objects that do not show large brightness variations, the colors are largely redder than solar in both B-R and R-I. The width of the color distribution may be intrinsic to the nature of the surfaces, but also could be that we are seeing irregularly shaped objects and measuring the colors at different times with just one telescope. For a smaller sample of objects we have observed with synchronized CCD cameras on the two telescopes. The CTIO 0.9-m observes in B, and MODEST in R. The CCD cameras are electronically linked together so that the start time and duration of observations are the same to better than 50 milliseconds. Thus the B-R color is a true measure of the surface of the debris piece facing the telescopes for that observation. Any change in color reflects a real change in the debris surface.

Seitzer, Patrick↗

NASA NTRS2009

Sizing of "Mother Ship and Catcher" Concepts for LEO Small Debris Capture

Most Low Earth Orbit (LEO) debris lies in a limited number of inclination "bands" associated with launch latitudes, or with specific useful orbit inclinations (such as polar orbits). Such narrow inclination bands generally have a uniform spread over all possible Right Ascensions of Ascending Node (RAANs), creating a different orbit plane for nearly every piece of debris. This complicates concept of rendezvous and capture for debris removal. However, a low-orbiting satellite will always phase in RAAN faster than debris objects in higher orbits at the same inclination, potentially solving the problem. Such a base can serve as a single space-based launch facility (a "mother ship") that can tend and then send tiny individual catcher devices for each debris object, as the facility drifts into the same RAAN as the higher object. This presentation will highlight characteristic system requirements of such an architecture, including structural and navigation requirements, power, mass and dV budgets for both the mother ship and the mass-produced common catcher devices that would clean out selected inclination bands. The altitude and inclination regime over which a band is to be cleared, the size distribution of the debris, and the inclusion of additional mission priorities all affect the sizing of the system. It is demonstrated that major LEO hazardous debris reductions can be realized in each band with a single LEO launch of a single mother ship, with simple attached catchers of total mass less than typical commercial LEO launch capability.

Bacon, John B.↗

NASA NTRS2009

Sizing of "Mother Ship and Catcher" Missions for LEO Small Debris and for GEO Large Object Capture

Most LEO debris lies in a limited number of inclination "bands" associated with specific useful orbits. Objects in such narrow inclination bands have all possible Right Ascensions of Ascending Node (RAANs), creating a different orbit plane for nearly every piece of debris. However, a low-orbiting satellite will always phase in RAAN faster than debris objects in higher orbits at the same inclination, potentially solving the problem. Such a low-orbiting base can serve as a "mother ship" that can tend and then send small, disposable common individual catcher/deboost devices--one for each debris object--as the facility drifts into the same RAAN as each higher object. The dV necessary to catch highly-eccentric orbit debris in the center of the band alternatively allows the capture of less-eccentric debris in a wider inclination range around the center. It is demonstrated that most LEO hazardous debris can be removed from orbit in three years, using a single LEO launch of one mother ship--with its onboard magazine of freeflying low-tech catchers--into each of ten identified bands, with second or potentially third launches into only the three highest-inclination bands. The nearly 1000 objects near the geostationary orbit present special challenges in mass, maneuverability, and ultimate disposal options, leading to a dramatically different architecture and technology suite than the LEO solution. It is shown that the entire population of near-GEO derelict objects can be gathered and tethered together within a 3 year period for future scrap-yard operations using achievable technologies and only two earth launches.

Bacon, John B.↗

NASA NTRS2010

Modeling of the Orbital Debris Population of RORSAT Sodium-Potassium Droplets

A large population resident in the orbital debris environment is composed of eutectic sodium-potassium (NaK) droplets, released during the reactor core ejection of 16 nuclear-powered Radar Ocean Reconnaissance Satellites (RORSATs) launched in the 1980s by the former Soviet Union. These electrically conducting RORSAT debris objects are spherical in shape, generating highly polarized radar returns. Their diameters are mostly in the centimeter and millimeter size regimes. Since the Space Surveillance Network catalog is limited to objects greater than 5 cm in low Earth orbit, our current knowledge about this special class of orbital debris relies largely on the analysis of Haystack radar data. This paper elaborates the simulation of the RORSAT debris populations in the new NASA Orbital Debris Engineering Model ORDEM2010, which replaces ORDEM2000. The estimation of the NaK populations uses the NASA NaK-module as a benchmark. It follows the general statistical approach to developing all other ORDEM2010-required LEO populations (for various types of debris and across a wide range of object sizes). This paper describes, in detail, each major step in the NaK-population derivation, including a specific discussion on the conversion between Haystack-measured radar-cross-sections and object-size distribution for the NaK droplets. Modeling results show that the RORSAT debris population is stable for the time period under study and that Haystack data sets are fairly consistent over the observations of multiple years.

Xu, Y.-L.↗

NASA NTRS2010

ORDEM2010 and MASTER-2009 Modeled Small Debris Population Comparison

The latest versions of the two premier orbital debris engineering models, NASA s ORDEM2010 and ESA s MASTER-2009, have been publicly released. Both models have gone through significant advancements since inception, and now represent the state-of-the-art in orbital debris knowledge of their respective agencies. The purpose of these models is to provide satellite designers/operators and debris researchers with reliable estimates of the artificial debris environment in near-Earth orbit. The small debris environment within the size range of 1 mm to 1 cm is of particular interest to both human and robotic spacecraft programs. These objects are much more numerous than larger trackable debris but are still large enough to cause significant, if not catastrophic, damage to spacecraft upon impact. They are also small enough to elude routine detection by existing observation systems (radar and telescope). Without reliable detection the modeling of these populations has always coupled theoretical origins with supporting observational data in different degrees. This paper details the 1 mm to 1 cm orbital debris populations of both ORDEM2010 and MASTER-2009; their sources (both known and presumed), current supporting data and theory, and methods of population analysis. Fluxes on spacecraft for chosen orbits are also presented and discussed within the context of each model.

Krisko, Paula H.↗

NASA NTRS2010

Optical Photometric Observations of GEO Debris

We report on a continuing program of optical photometric measurements of faint orbital debris at geosynchronous Earth orbit (GEO). These observations can be compared with laboratory studies of actual spacecraft materials in an effort to determine what the faint debris at GEO may be. We have optical observations from Cerro Tololo Inter-American Observatory (CTIO) in Chile of two samples of debris: 1. GEO objects discovered in a survey with the University of Michigan's 0.6-m aperture Curtis-Schmidt telescope MODEST (for Michigan Orbital DEbris Survey Telescope), and then followed up in real-time with the CTIO/SMARTS 0.9-m for orbits and photometry. Our goal is to determine 6 parameter orbits and measure colors for all objects fainter than R = 15 t11 magnitude that are discovered in the MODEST survey. 2. A smaller sample of high area to mass ratio (AMR) objects discovered independently, and acquired using predictions from orbits derived from independent tracking data collected days prior to the observations. Our optical observations in standard astronomical BVRI filters are done with either telescope, and with the telescope tracking the debris object at the object's angular rate. Observations in different filters are obtained sequentially. We have obtained 71 calibrated sequences of R-B-V-I-R magnitudes. A total of 66 of these sequences have 3 or more good measurements in all filters (not contaminated by star streaks or in Earth's shadow). Most of these sequences show brightness variations, but a small subset has observed brightness variations consistent with that expected from observational errors alone. The majority of these stable objects are redder than a solar color in both B-R and R-I. There is no dependence on color with brightness. For a smaller sample of objects we have observed with synchronized CCD cameras on the two telescopes. The CTIO 0.9-m observes in B, and MODEST in R. The CCD cameras are electronically linked together so that the start time and duration of observations are the same to better than 50 milliseconds. Thus, the B-R color is a true measure of the surface of the debris piece facing the telescopes for that observation. Any change in color reflects a real change in the debris surface. We will compare our observations with models and laboratory measurements of selected surfaces.

Seitzer, Patrick↗

NASA NTRS2012

Searching for Optically Faint GEO Debris

We report on results from a search for optically faint debris (defined as R > 20th magnitude, or smaller than 10 cm assuming an albedo of 0.175)) at geosynchronous orbit (GEO) using the 6.5-m Magellan telescope "Walter Baade" at Las Campanas Observatory in Chile. Our goal is to characterize the brightness distribution of debris to the faintest limiting magnitude possible. Our data was obtained during 6 hours of observing time during the photometric nights of 26 and 27 March 2011 with the IMACS f/2 instrument, which has a field of view (fov) of 0.5 degrees in diameter. All observations were obtained through a Sloan r filter, and calibrated by observations of Landolt standard stars. Our primary objective was to search for optically faint objects from one of the few known fragmentations at GEO: the Titan 3C Transtage (1968-081) fragmentation in 1992. Eight debris pieces and the parent rocket body are in the Space Surveillance Network public catalog. We successfully tracked two cataloged pieces of Titan debris with the 6.5-m telescope, followed by a survey for unknown objects on similar orbits but with different mean anomalies. To establish the bright end of the debris population, calibrated observations were acquired on the same field centers, telescope rates, and time period with a similar filter on the 0.6-m MODEST (Michigan Orbital DEbris Survey Telescope), located 100 km to the south of Magellan at Cerro Tololo Inter-American Observatory, Chile. We will show the calibrated brightness distributions from both telescopes, and compare the observed brightness distributions with that predicted for various population models of debris of different sizes.

Seitzer, Patrick↗

NASA NTRS2012

Debris Examination Using Ballistic and Radar Integrated Software

The Debris Examination Using Ballistic and Radar Integrated Software (DEBRIS) program was developed to provide rapid and accurate analysis of debris observed by the NASA Debris Radar (NDR). This software provides a greatly improved analysis capacity over earlier manual processes, allowing for up to four times as much data to be analyzed by one-quarter of the personnel required by earlier methods. There are two applications that comprise the DEBRIS system: the Automated Radar Debris Examination Tool (ARDENT) and the primary DEBRIS tool.

Griffith, Anthony↗

NASA NTRS2012

Data Acquisition, Management, and Analysis in Support of the Audiology and Hearing Conservation and the Orbital Debris Program Office

My internship at Johnson Space Center, Houston TX comprised of working simultaneously in the Space Life Science Directorate (Clinical Services Branch, SD3) in Audiology and Hearing Conservation and in the Astromaterials Research and Exploration Sciences Directorate in the Orbital Debris Program Office (KX). The purpose of the project done to support the Audiology and Hearing Conservation Clinic (AuHCon) is to organize and analyze auditory test data that has been obtained from tests conducted onboard the International Space Station (ISS) and in Johnson Space Center's clinic. Astronauts undergo a special type of auditory test called an On-Orbit Hearing Assessment (OOHA), which monitors hearing function while crewmembers are exposed to noise and microgravity during long-duration spaceflight. Data needed to be formatted to assist the Audiologist in studying, analyzing and reporting OOHA results from all ISS missions, with comparison to conventional preflight and post-flight audiometric test results of crewmembers. Orbital debris is the #1 threat to manned spacecraft; therefore NASA is investing in different measurement techniques to acquire information on orbital debris. These measurements are taken with telescopes in different parts of the world to acquire brightness variations over time, from which size, rotation rates and material information can be determined for orbital debris. Currently many assumptions are taken to resolve size and material from observed brightness, therefore a laboratory (Optical Measurement Center) is used to simulate the space environment and acquire information of known targets suited to best model the orbital debris population. In the Orbital Debris Program Office (ODPO) telescopic data were acquired and analyzed to better assess the orbital debris population.

Dicken, Todd↗

NASA NTRS2013

NASA Orbital Debris Large-Object Baseline Population in ORDEM 3.0

The NASA Orbital Debris Program Office (ODPO) has created and validated high fidelity populations of the debris environment for the latest Orbital Debris Engineering Model (ORDEM 3.0). Though the model includes fluxes of objects 10 um and larger, this paper considers particle fluxes for 1 cm and larger debris objects from low Earth orbit (LEO) through Geosynchronous Transfer Orbit (GTO). These are validated by several reliable radar observations through the Space Surveillance Network (SSN), Haystack, and HAX radars. ORDEM 3.0 populations were designed for the purpose of assisting, debris researchers and sensor developers in planning and testing. This environment includes a background derived from the LEO-to-GEO ENvironment Debris evolutionary model (LEGEND) with a Bayesian rescaling as well as specific events such as the FY-1C anti-satellite test, the Iridium 33/Cosmos 2251 accidental collision, and the Soviet/Russian Radar Ocean Reconnaissance Satellite (RORSAT) sodium-potassium droplet releases. The environment described in this paper is the most realistic orbital debris population larger than 1 cm, to date. We describe derivations of the background population and added specific populations. We present sample validation charts of our 1 cm and larger LEO population against Space Surveillance Network (SSN), Haystack, and HAX radar measurements.

Krisco, Paula H.↗

NASA NTRS2014

ORDEM 3.0 and MASTER-2009 Modeled Small Debris Population Comparison

The latest versions of the two premier orbital debris engineering models, NASA's ORDEM 3.0 and ESA's MASTER-2009, have been publically released. Both models have gone through significant advancements since inception, and now represent the state-of-the-art in orbital debris knowledge of their respective agencies. The purpose of these models is to provide satellite designers/operators and debris researchers with reliable estimates of the artificial debris environment in low Earth orbit (LEO) to geosynchronous orbit (GEO). The small debris environment within the size range of 1 mm to 1 cm is of particular interest to both human and robotic spacecraft programs, particularly in LEO. These objects are much more numerous than larger trackable debris and can have enough momentum to cause significant, if not catastrophic, damage to spacecraft upon impact. They are also small enough to elude routine detection by existing observation systems (radar and telescope). Without reliable detection the modeling of these populations has always coupled theoretical origins with supporting observational data in different degrees. In this paper, we present and detail the 1 mm to 1 cm orbital debris populations from both ORDEM 3.0 and MASTER-2009 in LEO. We review population categories: particle sources for MASTER-2009, particle densities for ORDEM 3.0. We describe data sources and their uses, and supporting models. Fluxes on spacecraft for chosen orbits are also presented and discussed within the context of each model.

Krisko, P. H.↗

NASA NTRS2014

The New NASA Orbital Debris Engineering Model ORDEM 3.0

The NASA Orbital Debris Program Office (ODPO) has released its latest Orbital Debris Engineering Model, ORDEM 3.0. It supersedes ORDEM 2000, now referred to as ORDEM 2.0. This newer model encompasses the Earth satellite and debris flux environment from altitudes of low Earth orbit (LEO) through geosynchronous orbit (GEO). Debris sizes of 10 micron through larger than 1 m in non-GEO and 10 cm through larger than 1 m in GEO are available. The inclusive years are 2010 through 2035. The ORDEM model series has always been data driven. ORDEM 3.0 has the benefit of many more hours of data from existing sources and from new sources than past ORDEM versions. The object data range in size from 10 μm to larger than 1 m, and include in situ and remote measurements. The in situ data reveals material characteristics of small particles. Mass densities are grouped in ORDEM 3.0 in terms of 'high-density', represented by 7.9 g/cc, 'medium-density' represented by 2.8 g/cc and 'low-density' represented by 1.4 g/cc. Supporting models have also advanced significantly. The LEO-to-GEO ENvironment Debris model (LEGEND) includes an historical and a future projection component with yearly populations that include launched and maneuvered intact spacecraft and rocket bodies, mission related debris, and explosion and collision event fragments. LEGEND propagates objects with ephemerides and physical characteristics down to 1 mm in size. The full LEGEND yearly population acts as an a priori condition for a Bayesian statistical model. Specific populations are added from sodium potassium droplet releases, recent major accidental and deliberate collisions, and known anomalous debris events. This paper elaborates on the upgrades of this model over previous versions. Sample validation results with remote and in situ measurements are shown, and the consequences of including material density are discussed as it relates to heightened risks to crewed and robotic spacecraft

Krisko, P. H.↗

NASA NTRS2016

Incidence of Debris Discs Around FGK Stars in the Solar Neighbourhood

Context. Debris discs are a consequence of the planet formation process and constitute the fingerprints of planetesimal systems. Their counterparts in the solar system are the asteroid and Edgeworth-Kuiper belts. Aims. The aim of this paper is to provide robust numbers for the incidence of debris discs around FGK stars in the solar neighborhood. Methods. The full sample of 177 FGK stars with d approx. less than 20 pc proposed for the DUst around NEarby Stars (DUNES) survey is presented. Herschel/PACS observations at 100 and 160 micrometers were obtained, and were complemented in some cases with data at 70 micrometers and at 250, 350, and 500 micrometer SPIRE photometry. The 123 objects observed by the DUNES collaboration were presented in a previous paper. The remaining 54 stars, shared with the Disc Emission via a Bias-free Reconnaissance in IR and Sub-mm (DEBRIS) consortium and observed by them, and the combined full sample are studied in this paper. The incidence of debris discs per spectral type is analyzed and put into context together with other parameters of the sample, like metallicity, rotation and activity, and age. Results. The subsample of 105 stars with d approx. less than 15 pc containing 23 F, 33 G, and 49 K stars is complete for F stars, almost complete for G stars, and contains a substantial number of K stars from which we draw solid conclusions on objects of this spectral type. The incidence rates of debris discs per spectral type are 0.26(+0.21/-0.14) (6 objects with excesses out of 23 F stars), 0.21(+0.17/-0.11) (7 out of 33 G stars), and 0.20(+0.14/-0.09) (10 out of 49 K stars); the fraction for all three spectral types together is 0.22(+0.08/-0.07) (23 out of 105 stars).The uncertainties correspond to a 95 confidence level. The medians of the upper limits of L(sub dust)/L(sub *) for each spectral type are 7.8 x 10(exp -7) (F), 1.4 x 10(exp -6) (G), and 2.2 x 10(exp -6) (K); the lowest values are around 4.0 x 10(exp -7). The incidence of debris discs is similar for active (young) and inactive (old) stars. The fractional luminosity tends to drop with increasing age, as expected from collisional erosion of the debris belts.

stars: late-type â€“ circumstellar matter â€“ prot↗

NASA NTRS2019

Development of a Model for the Small-Particle Orbital Debris Population Based on the STS Impact Record

In preparation for the release of the Orbital Debris Engineering Model (ORDEM) version 3.1, the NASA Orbital Debris Program Office (ODPO) revisited how orbiting debris populations of characteristic sizes smaller than 1 cm were modeled. The primary contributor to the population of sub-centimeter debris particles is the surface deterioration or erosion of spacecraft materials exposed to the outer-space environment. Because small particulates are not directly trackable by remote sensing, the primary means of detection is via historical counts of small impact features on flown radiator and window surfaces of the U.S. Space Transportation System (STS, also known as the Space Shuttle) from 1995-2011. Historic NASA studies of high-velocity impact tests have related impact-feature size to particle mass and velocity for certain STS surfaces, so that a corresponding particle size may be inferred from each small-impact feature observed. Micro-debris populations are then estimated by modeling the path and orientation of an STS mission through a simulated debris environment, and the densities of this simulated environment are rescaled to approximate the number of observed STS impact features. Monte-Carlo methods are further employed to gauge the estimation uncertainty of the rescaled environment. A description of the chosen methodologies for estimating and adjusting the micro-debris population model, and the results, are presented.

Seago, J..↗

NASA NTRSDate not supplied

Towards Real-time Global Assessment of Post-fire Debris Flow Hazard

As the risk of wildfires increases worldwide, burned steeplands are vulnerable to the secondary hazard of widespread sediment mobilization through debris flows. Following an initial burn, sediment and soil previously restrained by vegetation are no longer consolidated, allowing for easy mobilization into channels and along steep hillslopes through runoff. Sufficiently powerful rainfall incorporates entrained material into turbulent flows and serves as the primary trigger for debris flow initiation. There is thus an ongoing need to establish the relationship between rainfall and debris flow initiation based on a variety of spatiotemporal preconditions. Previous work establishes regional and local thresholds to constrain the effect of rainfall in recently burned areas, but no empirical or numerical solution has worldwide application. Building from regionally-based efforts in the U.S., this work considers how remote sensing data can be applied to better approximate the post-fire debris flow hazards worldwide using freely available global datasets and software. Our work assesses the utility of remote sensing resources for analyzing burn characteristics, topography, rainfall intensity/duration, and, thus, debris flow initiation. Early results show that global observations are sufficient to delineate background rainfall rates from storms likely to cause debris flows across a variety of burn severity and topographic conditions. However, the dearth of publicly-available post-fire debris flow inventories globally limit the ability to test how the model framework performs within different climatologic and morphologic areas. This work will present preliminary analysis over the Western United States and demonstrate the feasibility of a global, near-real time model to provide situational awareness of potential hazards within recently burned areas worldwide. Future work will also consider how global or regional precipitation forecasts may increase the lead time for improved early warning of these hazards.

Elijah Orland↗

NASA NTRSDate not supplied

Using Machine Learning to Infer Material Properties of Debris Fragments from X-ray Images in the DebriSat Project

The DebriSat project is a collaboration effort with the NASA Orbital Debris Program Office, the U.S. Space Force Space Systems Command Center, The Aerospace Corporation, and the University of Florida. To date, over 200,000 fragments from this ground-based, hypervelocity impact experiment have been collected, and processing is underway to determine their physical characteristics, such as material, shape, color, characteristic length, and average cross-sectional area. The x-ray process is primarily used to identify the location of the fragments and estimated size for extraction, so that these physical characteristics can be assessed. This paper proposes a machine learning-based approach to characterize materials from x-ray images of debris fragments embedded in soft-catch foam used in the DebriSat project. The novel methodology discussed in this paper will highlight the use of x-ray imagery data to characterize these fragments without extraction or a human-in-the-loop. Both supervised and unsupervised machine learning techniques are utilized with this approach to infer the physical parameters of the fragments embedded in the soft-catch foam panels used in the impact experiment based on x-ray images of the foam panels. Additionally, 3D reconstructions of the extracted fragments are created with images taken from two different angles using the structure from motion (SfM) method. The characteristic lengths and shape from the 3D reconstruction, alongside the physical characteristics of the debris, are used in the inference of the material type. To develop and test the approach, a dataset of x-ray images of debris fragments of varying sizes and materials is collected. Supervised learning methods such as convolutional neural networks (CNNs), support vector machines (SVM), decision trees, and random forest classifiers are used due to the high-dimensional feature spaces of the debris and nonlinear decision boundaries for material categorization. Given the limited pre-labeled data of embedded debris materials smaller than 10 mm, unsupervised machine learning techniques such as clustering algorithms and autoencoders are used, in addition to supervised learning methods. The clustering algorithms group similar fragments together based on their physical properties, and autoencoders reduce the dimensionality of the x ray images and extract relevant features. The performance of the proposed approach's is analyzed using a range of statistical methods, including confusion matrices, receiver operating characteristic curves, and precision-recall curves. The results are compared with those obtained using a baseline approach that relies on manual identification and classification of debris fragments. To evaluate the effectiveness of different machine learning methods, statistical tests such as t-tests, ANOVA, and cross-validation are performed, comparing the performance of CNNs, SVMs, clustering algorithms, and autoencoders. Additional analysis needs to be conducted to identify any sources of bias or variability that may affect the results, such as variations in imaging conditions or fragmentation patterns. Other topics explored are limitations, refinements, and the potential use of semi-supervised learning techniques, such as self-training to label unlabeled datasets and co-training using x-ray images taken from two different angles as two different models.

Saik Anam Siam↗

NASA NTRS2023

Using Machine Learning to Infer Material Properties of Debris Fragments from X-ray Images in the DebriSat Project

Saik Anam Siam↗

NASA NTRS2016

Lightforce Photon-Pressure Collision Avoidance: Efficiency Analysis in the Current Debris Environment and Long-Term Simulation Perspective

This work provides an efficiency analysis of the LightForce space debris collision avoidance scheme in the current debris environment and describes a simulation approach to assess its impact on the long-term evolution of the space debris environment. LightForce aims to provide just-in-time collision avoidance by utilizing photon pressure from ground-based industrial lasers. These ground stations impart minimal accelerations to increase the miss distance for a predicted conjunction between two objects. In the first part of this paper we will present research that investigates the short-term effect of a few systems consisting of 20-kilowatt-class lasers directed by 1.5-meter-diameter telescopes using adaptive optics. The results found such a network of ground stations to mitigate more than 85 percent of conjunctions and could lower the expected number of collisions in Low Earth Orbit (LEO) by an order of magnitude. While these are impressive numbers that indicate LightForce's utility in the short-term, the remaining 15 percent of possible collisions contain (among others) conjunctions between two massive objects that would add large amount of debris if they collide. Still, conjunctions between massive objects and smaller objects can be mitigated. Hence, we choose to expand the capabilities of the simulation software to investigate the overall effect of a network of LightForce stations on the long-term debris evolution. In the second part of this paper, we will present the planned simulation approach for that effort. For the efficiency analysis of collision avoidance in the current debris environment, we utilize a simulation approach that uses the entire Two Line Element (TLE) catalog in LEO for a given day as initial input. These objects are propagated for one year and an all-on-all conjunction analysis is performed. For conjunctions that fall below a range threshold, we calculate the probability of collision and record those values. To assess efficiency, we compare a baseline (without collision avoidance) conjunction analysis with an analysis where LightForce is active. Using that approach, we take into account that collision avoidance maneuvers could have effects on third objects. Performing all-on-all conjunction analyses for extended period of time requires significant computer resources; hence we implemented this simulation utilizing a highly parallel approach on the NASA Pleiades supercomputer.

space debris mitigation↗