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NASA NTRS2016

The NASA/AFRL Meter Class Autonomous Telescope

For the past decade, the NASA Orbital Debris Program Office (ODPO) has relied on using various ground-based telescopes in Chile to acquire statistical survey data as well as photometric and spectroscopic data of orbital debris in geosynchronous Earth orbit (GEO). The statistical survey data have been used to supply the Orbital Debris Engineering Model (ORDEM) v.3.0 with debris detections in GEO to better model the environment at altitudes where radar detections are limited. The data produced for the statistical survey ranged from 30 to 40 nights per year, which only accounted for ~10% of the possible observing time. Data collection was restricted by ODPO resources and weather conditions. In order to improve the statistical sampling in GEO, as well as observe and sample other orbits, NASA's ODPO with support from the Air Force Research Laboratory (AFRL), has constructed a new observatory dedicated to orbital debris - the Meter Class Autonomous Telescope (MCAT) on Ascension Island. This location provides MCAT with the unique ability to access targets orbiting at an altitude of less than 1,000 km and low inclinations (< 20 deg). This orbital regime currently has little to no coverage by the U.S. Space Surveillance Network. Unlike previous ODPO optical assets, the ability to operate autonomously will allow rapid response observations of break-up events, an observing mode that was only available via radar tasking prior to MCAT's deployment. The primary goal of MCAT is to statistically characterize GEO via daily tasking files uploaded from ODPO. These tasking files define which operating mode to follow, providing the field center, rates, and/or targets to observe over the entire observing period. The system is also capable of tracking fast-moving targets in low Earth orbit (LEO), middle Earth orbit (MEO), as well as highly eccentric orbits like geostationary transfer orbits. On 25 August 2015, MCAT successfully acquired scientific first light, imaging the Bug Nebula and tracked objects in LEO, MEO, and GEO. NASA is working towards characterizing the system and thoroughly testing the integrated hardware and software control to achieve fully autonomous operations by late 2016. This paper will review the history and current status of the MCAT project, the details of the telescope system, and its five currently manifested operating modes.

Cowardin, H.↗
DOE OSTI2026

Automatic Calibration and Health Monitoring of Infrastructure Sensors

Smart transportation infrastructure relies on networks of heterogeneous sensors - cameras, radars, and lidars - continuously monitoring traffic conditions. However, executing the initial spatial calibration of multiple sensors and the subsequent health monitoring presents significant operational challenges. Environmental factors, mechanical vibrations, and gradual drift cause spatial misalignment, degrading fusion performance and tracking accuracy. Traditional calibration approaches require manual intervention with specialized targets or survey equipment, resulting in service interruptions and high maintenance costs. This work presents an automated framework for initial calibration and continuous health monitoring without human intervention or service disruption. Our approach addresses two critical problems: (1) detecting when sensors become miscalibrated during operation, and (2) automatically re-establishing spatial alignment using only operational traffic data. The health monitoring component analyzes measurement innovations - differences between sensor observations and predicted object states - to detect systematic biases indicative of calibration drift. By computing bias magnitude, directional consistency, and rejection rates, the system identifies miscalibrations as small as 0.5 meters. Unlike traditional methods requiring known calibration targets, our diagnostic operates continuously on live traffic observations, enabling early detection before fusion quality degrades. The automatic recalibration algorithm leverages overlapping sensor fields-of-view and temporal correlation of vehicle observations. Using graph-based optimization, the system automatically discovers which sensor pairs observe common regions, estimates pairwise spatial transformations using RANSAC-based robust estimation, and jointly optimizes all sensor poses through bundle adjustment. The framework handles practical deployment challenges, including different sensor sampling rates (1-10 Hz), varying installation positions, unknown orientations, and limited overlap regions (>10%). When approximate sensor positions are available from installation surveys (+/-1m accuracy), the algorithm additionally estimates sensor orientations, refining both position and rotation to sub-meter and sub-degree accuracy. We validate the framework on multi-hour traffic datasets from six heterogeneous sensors with sampling rates ranging from 1 Hz to 10 Hz. Results demonstrate successful calibration even with sparse overlap (<20%) and automatic detection of miscalibrations exceeding 0.8 meters. This work enables a "deploy-and-forget" sensor infrastructure that maintains calibration autonomously, reducing maintenance costs while improving tracking accuracy. The techniques generalize beyond transportation to any multi-sensor monitoring application requiring robust spatial alignment, including smart cities, industrial monitoring, and surveillance systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2006

Earth Satellite Population Instability: Underscoring the Need for Debris Mitigation

A recent study by NASA indicates that the implementation of international orbital debris mitigation measures alone will not prevent a significant increase in the artificial Earth satellite population, beginning in the second half of this century. Whereas the focus of the aerospace community for the past 25 years has been on the curtailment of the generation of long-lived orbital debris, active remediation of the current orbital debris population should now be reconsidered to help preserve near-Earth space for future generations. In particular, we show in this paper that even if launch operations were to cease today, the population of space debris would continue to grow. Further, proposed remediation techniques do not appear to offer a viable solution. We therefore recommend that, while the aerospace community maintains the current debris-limiting mission regulations and postmission disposal procedures, future emphasis should be placed on finding new remediation technologies for solving this growing problem. Since the launch of Sputnik 1, space activities have created an orbital debris environment that poses increasing impact risks to existing space systems, including human space flight and robotic missions (1, 2). Currently, more than 9,000 Earth orbiting man-made objects (including many breakup fragments), with a combined mass exceeding 5 million kilograms, are tracked by the US Space Surveillance Network and maintained in the US satellite catalog (3-5). Three accidental collisions between cataloged satellites during the period from late 1991 to early 2005 have already been documented (6), although fortunately none resulted in the creation of large, trackable debris clouds. Several studies conducted during 1991-2001 demonstrated, with assumed future launch rates, the unintended growth potential of the Earth satellite population, resulting from random, accidental collisions among resident space objects (7-13). In some low Earth orbit (LEO) altitude regimes where the number density of satellites is above a critical spatial density, the production rate of new satellites (i.e., debris) due to collisions exceeds the loss of objects due to orbital decay. NASA s evolutionary satellite population model LEGEND (LEO-to-GEO Environment Debris model), developed by the Orbital Debris Program Office at the NASA Lyndon B. Johnson Space Center, is a high fidelity three-dimensional physical model that is capable of simulating the historical satellite environment, as well as the evolution of future debris populations (14, 15). The subject study assumed no rocket bodies and spacecraft were launched after December 2004, and no future disposal maneuvers were allowed for existing spacecraft, few of which currently have such a capability. The rate of satellite explosions would naturally decrease to zero within a few decades as the current satellite population ages. The LEGEND future projection adopts a Monte Carlo approach to simulate future on-orbit explosions and collisions. Within a given projection time step, once the explosion probability is estimated for an intact object, a random number is drawn and compared with the probability to determine if an explosion would occur. A similar procedure is applied to collisions for each pair of target and projectile involved within the same time step. Due to the nature of the Monte Carlo process, multiple projection runs must be performed and analyzed before one can draw reliable and meaningful conclusions from the outcome. A total of fifty, 200-year future projection Monte Carlo simulations were executed and evaluated (16).

Liou, Jer-chyi↗
NASA NTRS1995

TAOS Orbit Determination Results Using Global Positioning Satellites

Orbit determination results for the Air Force Phillips Laboratory's Technology for Autonomous Operational Survivability (TAOS) satellite using a Rockwell AST V Global Positioning System (GPS) receiver are presented in this paper. Under a cooperative effort, GPS orbit determination technology developed at Jet Propulsion Laboratory (JPL) has been transferred to the U.S. Air Force. JPL's post processing differential GPS software MIRAGE [1] was modified to perform precise orbit determination for the TAOS satellite. Reconstructed TAOS position accuracies of 10 meters (3 sigma) are the objective. With four days of data, three-dimensional positions of less than 3 meters (1 sigma) have been achieved with overlapping orbit determination spans. Orbit determination results are also compared with those of the on-board GPS receiver's navigation solutions and with the Air Force's Satellite Control Network SGLS processing.

TAOS↗
NASA NTRS1991

Fuzzy set methods for object recognition in space applications

During the reporting period, the development of the theory and application of methodologies for decision making under uncertainty was addressed. Two subreports are included; the first on properties of general hybrid operators, while the second considers some new research on generalized threshold logic units. In the first part, the properties of the additive gamma-model, where the intersection part is first considered to be the product of the input values and the union part is obtained by an extension of De Morgan's law to fuzzy sets, is explored. Then the Yager's class of union and intersection is used in the additive gamma-model. The inputs are weighted to some power that represents their importance and thus their contribution to the compensation process. In the second part, the extension of binary logic synthesis methods to multiple valued logic synthesis methods to enable the synthesis of decision networks when the input/output variables are not binary is discussed.

Keller, James M.↗
NASA NTRS1981

Consolidation of NASA tracking stations into a single ground network in the TDRSS era

NASA has operated two separate worldwide ground-based tracking and data acquisition networks for support of its various missions. The Spaceflight Tracking and Data Network (STDN) has provided support to all NASA earth orbiting spacecraft. The Deep Space Network (DSN) supports almost exclusively those unmanned exploratory spacecraft which have been sent far from earth. The Tracking and Data Relay Satellite System (TDRSS), which is conceptually a part of the STDN, will soon be added to the first two networks. The TDRSS will consist of two geosynchronous satellites together with a single ground terminal in White Sands, New Mexico. The TDRSS was conceived as a means of providing improved tracking and data relay service for a large class of the earth orbiting satellites. An investigation was conducted with the objective to reduce the costs of providing support to those spacecraft which were not TDRS-compatible. It was recommended that the core sites of the Ground segment of the STDN (GSTDN) be consolidated into the DSN

Layland, J. W.↗
NASA NTRS2001

Activities on Space Debris in U.S.

In the U.S. space debris activities are addressed at all government levels, from the Executive Office of the President to the individual federal agencies to specialized centers, laboratories, organizations, and research groups. U.S. Space Policy specifically challenges government agencies to seek to minimize the creation of space debris and to promote debris minimization practices both domestically and internationally. A set of space debris mitigation standard practices has been developed and adopted by relevant US government agencies, and their application by the commercial aerospace community is highly encouraged. A growing number of US government agencies have issued their own space debris mitigation policies, directives, regulations, and standards. Space debris research, including the definition and modeling of the current and future near-Earth space environment and the development of debris protection technologies, is principally conducted by NASA and the Department of Defense. The U.S. Space Surveillance Network continues to provide the most complete and timely characterization of the population of space debris larger than 10 cm. During the past several years major advancements have been achieved in extending this environment definition in LEO to include particles as small as only a few millimeters. The inspection of returned spacecraft surfaces continues to shed light on the even smaller debris population. With improvements in computer technology, new and more capable programs have been and are being developed to solve a number of operational and research problems. Finally, the academic and industrial sectors of the U.S. are also increasing their participation in and contributions to space debris operations and research. The cooperation of satellite and launch vehicle developers and operators is essential to the U.S. objective of promoting the preservation of the space environment for future generations.

Johnson, Nicholas L.↗
NASA NTRS2010

MaROS Strategic Relay Planning and Coordination Interfaces

The Mars Relay Operations Service (MaROS) is designed to provide planning and analysis tools in support of ongoing Mars Network relay operations. Strategic relay planning requires coordination between lander and orbiter mission ground data system (GDS) teams to schedule and execute relay communications passes. MaROS centralizes this process, correlating all data relevant to relay coordination to provide a cohesive picture of the relay state. Service users interact with the system through thin-layer command line and web user interface client applications. Users provide and utilize data such as lander view periods of orbiters, Deep Space Network (DSN) antenna tracks, and reports of relay pass performance. Users upload and download relevant relay data via formally defined and documented file structures including some described in Extensible Markup Language (XML). Clients interface with the system via an http-based Representational State Transfer (ReST) pattern using Javascript Object Notation (JSON) formats. This paper will provide a general overview of the service architecture and detail the software interfaces and considerations for interface design.

Allard, Daniel A.↗
NASA NTRS2004

Masked Proportional Routing

Masked proportional routing is an improved procedure for choosing links between adjacent nodes of a network for the purpose of transporting an entity from a source node ("A") to a destination node ("B"). The entity could be, for example, a physical object to be shipped, in which case the nodes would represent waypoints and the links would represent roads or other paths between waypoints. For another example, the entity could be a message or packet of data to be transmitted from A to B, in which case the nodes could be computer-controlled switching stations and the links could be communication channels between the stations. In yet another example, an entity could represent a workpiece while links and nodes could represent, respectively, manufacturing processes and stages in the progress of the workpiece towards a finished product. More generally, the nodes could represent states of an entity and the links could represent allowed transitions of the entity. The purpose of masked proportional routing and of related prior routing procedures is to schedule transitions of entities from their initial states ("A") to their final states ("B") in such a manner as to minimize a cost or to attain some other measure of optimality or efficiency. Masked proportional routing follows a distributed (in the sense of decentralized) approach to probabilistically or deterministically choosing the links. It was developed to satisfy a need for a routing procedure that 1. Does not always choose the same link(s), even for two instances characterized by identical estimated values of associated cost functions; 2. Enables a graceful transition from one set of links to another set of links as the circumstances of operation of the network change over time; 3. Is preferably amenable to separate optimization of different portions of the network; 4. Is preferably usable in a network in which some of the routing decisions are made by one or more other procedure(s); 5. Preferably does not cause an entity to visit the same node twice; and 6. Preferably can be modified so that separate entities moving from A to B do not arrive out of order.

Wolpert, David↗
NASA NTRS2010

Route Generation for a Synthetic Character (BOT) Using a Partial or Incomplete Knowledge Route Generation Algorithm in UT2004 Virtual Environment

This paper presents a new Route Generation Algorithm that accurately and realistically represents human route planning and navigation for Military Operations in Urban Terrain (MOUT). The accuracy of this algorithm in representing human behavior is measured using the Unreal Tournament(Trademark) 2004 (UT2004) Game Engine to provide the simulation environment in which the differences between the routes taken by the human player and those of a Synthetic Agent (BOT) executing the A-star algorithm and the new Route Generation Algorithm can be compared. The new Route Generation Algorithm computes the BOT route based on partial or incomplete knowledge received from the UT2004 game engine during game play. To allow BOT navigation to occur continuously throughout the game play with incomplete knowledge of the terrain, a spatial network model of the UT2004 MOUT terrain is captured and stored in an Oracle 11 9 Spatial Data Object (SOO). The SOO allows a partial data query to be executed to generate continuous route updates based on the terrain knowledge, and stored dynamic BOT, Player and environmental parameters returned by the query. The partial data query permits the dynamic adjustment of the planned routes by the Route Generation Algorithm based on the current state of the environment during a simulation. The dynamic nature of this algorithm more accurately allows the BOT to mimic the routes taken by the human executing under the same conditions thereby improving the realism of the BOT in a MOUT simulation environment.

Hanold, Gregg T.↗
NASA NTRS2011

Evaluating the Use of Remote Sensing Data in the USAID Famine Early Warning Systems Network

The US Agency for International Development (USAID) s Famine Early Warning System Network (FEWS NET) provides monitoring and early warning support to decision makers responsible for responding to food insecurity emergencies on three continents. FEWS NET uses satellite remote sensing and ground observations of rainfall and vegetation in order to provide information on drought, floods and other extreme weather events to decision makers. Previous research has presented results from a professional review questionnaire with FEWS NET expert end-users whose focus was to elicit Earth observation requirements. The review provided FEWS NET operational requirements and assessed the usefulness of additional remote sensing data. Here we analyzed 1342 food security update reports from FEWS NET. The reports consider the biophysical, socioeconomic, and contextual influences on the food security in 17 countries in Africa from 2000-2009. The objective was to evaluate the use of remote sensing information in comparison with other important factors in the evaluation of food security crises. The results show that all 17 countries use rainfall information, agricultural production statistics, food prices and food access parameters in their analysis of food security problems. The reports display large scale patterns that are strongly related to history of the FEWS NET program in each country. We found that rainfall data was used 84% of the time, remote sensing of vegetation 28% of the time, and gridded crop models 10%, reflecting the length of use of each product in the regions. More investment is needed in training personnel on remote sensing products to improve use of data products throughout the FEWS NET system.

Brown, Molly E.↗
NASA NTRS2012

Evaluating the Use of Remote Sensing Data in the U.S. Agency for International Development Famine Early Warning Systems Network

The U.S. Agency for International Development (USAID)'s Famine Early Warning System Network (FEWS NET) provides monitoring and early warning support to decision makers responsible for responding to food insecurity emergencies on three continents. FEWS NET uses satellite remote sensing and ground observations of rainfall and vegetation in order to provide information on drought, floods, and other extreme weather events to decision makers. Previous research has presented results from a professional review questionnaire with FEWS NET expert end-users whose focus was to elicit Earth observation requirements. The review provided FEWS NET operational requirements and assessed the usefulness of additional remote sensing data. We analyzed 1342 food security update reports from FEWS NET. The reports consider the biophysical, socioeconomic, and contextual influences on the food security in 17 countries in Africa from 2000 to 2009. The objective was to evaluate the use of remote sensing information in comparison with other important factors in the evaluation of food security crises. The results show that all 17 countries use rainfall information, agricultural production statistics, food prices, and food access parameters in their analysis of food security problems. The reports display large-scale patterns that are strongly related to history of the FEWS NET program in each country. We found that rainfall data were used 84% of the time, remote sensing of vegetation 28% of the time, and gridded crop models 10% of the time, reflecting the length of use of each product in the regions. More investment is needed in training personnel on remote sensing products to improve use of data products throughout the FEWS NET system.

USAID↗
NASA NTRS2004

Scientific Objectives, Measurement Needs, and Challenges Motivating the PARAGON Aerosol Initiative

Aerosols are involved in a complex set of processes that operate across many spatial and temporal scales. Understanding these processes, and ensuring their accurate representation in models of transport, radiation transfer, and climate, requires knowledge of aerosol physical, chemical, and optical properties and the distributions of these properties in space and time. To derive aerosol climate forcing, aerosol optical and microphysical properties and their spatial and temporal distributions, and aerosol interactions with clouds, need to be understood. Such data are also required in conjunction with size-resolved chemical composition in order to evaluate chemical transport models and to distinguish natural and anthropogenic forcing. Other basic parameters needed for modeling the radiative influences of aerosols are surface reflectivity and three-dimensional cloud fields. This large suite of parameters mandates an integrated observing and modeling system of commensurate scope. The Progressive Aerosol Retrieval and Assimilation Global Observing Network (PARAGON) concept, designed to meet this requirement, is motivated by the need to understand climate system sensitivity to changes in atmospheric constituents, to reduce climate model uncertainties, and to analyze diverse collections of data pertaining to aerosols. This paper highlights several challenges resulting from the complexity of the problem. Approaches for dealing with them are offered in the set of companion papers.

optical depth↗
NASA NTRS1990

Advanced systems engineering and network planning support

The objective of this task was to take a fresh look at the NASA Space Network Control (SNC) element for the Advanced Tracking and Data Relay Satellite System (ATDRSS) such that it can be made more efficient and responsive to the user by introducing new concepts and technologies appropriate for the 1997 timeframe. In particular, it was desired to investigate the technologies and concepts employed in similar systems that may be applicable to the SNC. The recommendations resulting from this study include resource partitioning, on-line access to subsets of the SN schedule, fluid scheduling, increased use of demand access on the MA service, automating Inter-System Control functions using monitor by exception, increase automation for distributed data management and distributed work management, viewing SN operational control in terms of the OSI Management framework, and the introduction of automated interface management.

Walters, David H.↗
NASA NTRS2021

Assessing Relay Communications for Mars Sample Return Surface Mission Concepts

The Mars Sample Return (MSR) Campaign is a 3-mission campaign concept supported by NASA and ESA to return samples from the Mars surface. MSR will, for the firsttime ever, present a need to communicate with multiple surfaceassets that are co-located on Mars in a coordinated effort toaccomplish the unified objective of fetching, transporting, andreturning samples from Mars. Currently, Mars surface assetsrelay data to and from Earth using a number of orbiters inwhat’s known as the Mars Relay Network (MRN). This networkis characterized by a small number of surface assets distributedacross the Martian globe and a larger number of orbiters toprovide relay services. As of June 2020, there are two surfaceassets for which five orbiters are providing relay. During theMSR Campaign, there will be two rovers and a lander that allwill require relay communication from a small number of Marsorbiters to meet the aggressive MSR timeline. The inversion ofthe current MRN paradigm, a system of many surface assetsrequiring relay and few orbiters to provide relay, necessitatesthe unique challenge of optimally allocating relay passes tomaximize the operational capability of all assets. The allocationmust consider a large number of trade variables includingMars asset operational requirements and Earth ground systemconstraints, including staffing schedules, operations planningacross time zones, and more. To address these telecommunicationchallenges, the Mars Asset Relay Mission Link AllocationDesign Environment (MARMLADE) tool was developed. Itis a MATLAB-based tool to assign orbiter passes or Direct-From-Earth (DFE) links to each of the three surface assets andquantify the operational efficiency of each surface asset.MARMLADE uses a data set of simulated Mars relay orbitergeometry and telecommunication capabilities provided by JPL’sTelecom Orbit Analysis and Simulation Tool (TOAST) softwareto compute which asset should get each pass based on a seriesof heuristics and predictions of all assets’ states. WithinMARMLADE, the user can provide inputs including the optionfor time-based pass splitting, fixed FWD data rate capabilities,DFE communication capabilities, and link parameters allowingfor the assessment of complex operations and hardware tradesusing surface mission operational efficiency as a primary figureof merit. As the MSR mission concepts continue to mature,MARMLADE is being used to assess ability of all MSR elementsto meet the surface mission timeline requirements and to provide relay link allocations to each of the MSR surface assets.

Lee, Charles↗
NASA NTRS1991

Geostationary Operational Environmental Satellite (GOES I-M) METSAT project

The primary objective of the METSAT project is to provide a satellite system that meets the National Environmental Satellite Data and Information Service (NESDIS) requirements as specified by NOAA. For the GOES I-M spacecraft, these requirements include an imager and sounder system, a data collection system, and a search and rescue system. The Space Transportation System and GOES I-M development philosophy and the satellite transfer orbit philosophy are explained. The spacecraft will be launched from the Kennedy Space Center using Atlas G/Centaur D-1A expendable launch vehicles. The coverage required for launch and the support of transfer and drift orbits will consist of the 26-m antenna as prime and the TBD antenna as backup for 11 days at all complexes. There will be contingency support 15 days for on-station spacecraft checkout. After the initial 30 to 45 days, the Deep Space Network (DSN) is committed for emergency support. Contingency and emergency support will be provided by Goldstone only. Information is given in tabular form for DSN support, frequency assignments, telemetry, command, and tracking support responsibility.

Blaney, K.↗
NASA NTRS1994

Portable parallel stochastic optimization for the design of aeropropulsion components

This report presents the results of Phase 1 research to develop a methodology for performing large-scale Multi-disciplinary Stochastic Optimization (MSO) for the design of aerospace systems ranging from aeropropulsion components to complete aircraft configurations. The current research recognizes that such design optimization problems are computationally expensive, and require the use of either massively parallel or multiple-processor computers. The methodology also recognizes that many operational and performance parameters are uncertain, and that uncertainty must be considered explicitly to achieve optimum performance and cost. The objective of this Phase 1 research was to initialize the development of an MSO methodology that is portable to a wide variety of hardware platforms, while achieving efficient, large-scale parallelism when multiple processors are available. The first effort in the project was a literature review of available computer hardware, as well as review of portable, parallel programming environments. The first effort was to implement the MSO methodology for a problem using the portable parallel programming language, Parallel Virtual Machine (PVM). The third and final effort was to demonstrate the example on a variety of computers, including a distributed-memory multiprocessor, a distributed-memory network of workstations, and a single-processor workstation. Results indicate the MSO methodology can be well-applied towards large-scale aerospace design problems. Nearly perfect linear speedup was demonstrated for computation of optimization sensitivity coefficients on both a 128-node distributed-memory multiprocessor (the Intel iPSC/860) and a network of workstations (speedups of almost 19 times achieved for 20 workstations). Very high parallel efficiencies (75 percent for 31 processors and 60 percent for 50 processors) were also achieved for computation of aerodynamic influence coefficients on the Intel. Finally, the multi-level parallelization strategy that will be needed for large-scale MSO problems was demonstrated to be highly efficient. The same parallel code instructions were used on both platforms, demonstrating portability. There are many applications for which MSO can be applied, including NASA's High-Speed-Civil Transport, and advanced propulsion systems. The use of MSO will reduce design and development time and testing costs dramatically.

Sues, Robert H.↗
NASA NTRS1996

SSME Condition Monitoring Using Neural Networks and Plume Spectral Signatures

For a variety of reasons, condition monitoring of the Space Shuttle Main Engine (SSME) has become an important concern for both ground tests and in-flight operation. The complexities of the SSME suggest that active, real-time condition monitoring should be performed to avoid large-scale or catastrophic failure of the engine. In 1986, the SSME became the subject of a plume emission spectroscopy project at NASA's Marshall Space Flight Center (MSFC). Since then, plume emission spectroscopy has recorded many nominal tests and the qualitative spectral features of the SSME plume are now well established. Significant discoveries made with both wide-band and narrow-band plume emission spectroscopy systems led MSFC to develop the Optical Plume Anomaly Detection (OPAD) system. The OPAD system is designed to provide condition monitoring of the SSME during ground-level testing. The operational health of the engine is achieved through the acquisition of spectrally resolved plume emissions and the subsequent identification of abnormal emission levels in the plume indicative of engine erosion or component failure. Eventually, OPAD, or a derivative of the technology, could find its way on to an actual space vehicle and provide in-flight engine condition monitoring. This technology step, however, will require miniaturized hardware capable of processing plume spectral data in real-time. An objective of OPAD condition monitoring is to determine how much of an element is present in the SSME plume. The basic premise is that by knowing the element and its concentration, this could be related back to the health of components within the engine. For example, an abnormal amount of silver in the plume might signify increased wear or deterioration of a particular bearing in the engine. Once an anomaly is identified, the engine could be shut down before catastrophic failure occurs. Currently, element concentrations in the plume are determined iteratively with the help of a non-linear computer code called SPECTRA, developed at the USAF Arnold Engineering Development Center. Ostensibly, the code produces intensity versus wavelength plots (i.e., spectra) when inputs such as element concentrations, reaction temperature, and reaction pressure are provided. However, in order to provide a higher-level analysis, element concentration is not specified explicitly as an input. Instead, two quantum variables, number density and broadening parameter, are used. Past experience with OPAD data analysis has revealed that the region of primary interest in any SSME plume spectrum lies in the wavelength band of 3300 A to 4330 A. Experience has also revealed that some elements, such as iron, cobalt and nickel, cause multiple peaks over the chosen wavelength range whereas other elements (magnesium, for example) have a few, relatively isolated peaks in the chosen wavelength range. Iteration with SPECTRA as a part of OPAD data analysis is an incredibly labor intensive task and not one to be performed by hand. What is really needed is the "inverse" of the computer code but the mathematical model for the inverse mapping is tenuous at best. However, building generalized models based upon known input/output mappings while ignoring details of the governing physical model is possible using neural networks. Thus the objective of the research project described herein was to quickly and accurately predict combustion temperature and element concentrations (i.e., number density and broadening parameter) from a given spectrum using a neural network. In other words, a neural network had to be developed that would provide a generalized "inverse" of the computer code SPECTRA.

Hopkins, Randall↗