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NASA NTRS2018

International Space Station Medical Projects - Full Services to Mars

The International Space Station Medical Projects (ISSMP) Element provides planning, integration, and implementation services for HRP research studies for both spaceflight and flight analog research. Through the implementation of these two efforts, ISSMP offers an innovative way of guiding research decisions to meet the unique challenges of understanding the human risks to space exploration. Flight services provided by ISSMP include leading informed consent briefings, developing and validating in-flight crew procedures, providing ISS crew and ground-controller training, real-time experiment monitoring, on-orbit experiment and hardware operations and facilitating data transfer to investigators. For analog studies at the NASA Human Exploration Research Analog (HERA), the ISSMP team provides subject recruitment and screening, science requirements integration, data collection schedules, data sharing agreements, mission scenarios and facilities to support investigators. The ISSMP also serves as the HRP interface to external analog providers including the :envihab bed rest facility (Cologne, Germany), NEK isolation chamber (Moscow, Russia) and the Antarctica research stations. Investigators working in either spaceflight or analog environments requires a coordinated effort between NASA and the investigators. The interdisciplinary nature of both flight and analog research requires investigators to be aware of concurrent research studies and take into account potential confounding factors that may impact their research objectives. Investigators must define clear research requirements, participate in Investigator Working Group meetings, obtain human use approvals, and provide study-specific training, sample and data collection and procedures all while adhering to schedule deadlines. These science requirements define the technical, functional and performance operations to meet the research objectives. The ISSMP maintains an expert team of professionals with the knowledge and experience to guide investigators science through all aspects of mission planning, crew operations, and research integration. During this session, the ISSMP team will discuss best-practices approaches for successfully preparing and conducting studies in both the flight and analog environments. Critical tips and tricks will be shown to greatly improve your chances of successfully completing your research aboard the International Space Station and in Spaceflight Analogs.

Pietrzyk, R. A.↗
NASA NTRS2004

Hybrid Exploration Agent Platform and Sensor Web System

A sensor web to collect the scientific data needed to further exploration is a major and efficient asset to any exploration effort. This is true not only for lunar and planetary environments, but also for interplanetary and liquid environments. Such a system would also have myriad direct commercial spin-off applications. The Hybrid Exploration Agent Platform and Sensor Web or HEAP-SW like the ANTS concept is a Sensor Web concept. The HEAP-SW is conceptually and practically a very different system. HEAP-SW is applicable to any environment and a huge range of exploration tasks. It is a very robust, low cost, high return, solution to a complex problem. All of the technology for initial development and implementation is currently available. The HEAP Sensor Web or HEAP-SW consists of three major parts, The Hybrid Exploration Agent Platforms or HEAP, the Sensor Web or SW and the immobile Data collection and Uplink units or DU. The HEAP-SW as a whole will refer to any group of mobile agents or robots where each robot is a mobile data collection unit that spends most of its time acting in concert with all other robots, DUs in the web, and the HEAP-SWs overall Command and Control (CC) system. Each DU and robot is, however, capable of acting independently. The three parts of the HEAP-SW system are discussed in this paper. The Goals of the HEAP-SW system are: 1) To maximize the amount of exploration enhancing science data collected; 2) To minimize data loss due to system malfunctions; 3) To minimize or, possibly, eliminate the risk of total system failure; 4) To minimize the size, weight, and power requirements of each HEAP robot; 5) To minimize HEAP-SW system costs. The rest of this paper discusses how these goals are attained.

Stoffel, A. William↗
NASA NTRS1975

NOAA requirements and programs

Service programs in NOAA that contemplate using the Geostationary Operational Environmental Satellite (GEOS) Data Collection System (DCS) are considered. The GEOS DCS will be operated by the National Environmental Satellite Service of NOAA as an integral part of the national operation environmental satellite program. This plan is concerned with that part of the GEOS program connected with collection and relay of data from remote locations. Service programs include: (1) hydrological data collection; (2) oceanographic data collection; (3) marine observations from data buoys; (4) Tsunami warning service; and (5) meteorological service.

Flanders, A. F.↗
NASA NTRS2005

Giovanni: A System for Rapid Access, Visualization and Analysis of Earth Science Data Online

Collecting data and understanding data structures traditionally are the first steps that a user must take, before the core investigation can begin. This is a time-consuming and challenging task, especially when science objectives require users to deal with large multi-sensor data that are usually in different formats and internal structures. The Goddard Earth Sciences Data and Information Services Center (GES DISC) has created the GES DISC Interactive Online Visualization and ANalysis Infrastructure, Giovanni, to enable Web-based visualization and analysis of satellite remotely sensed meteorological, oceanographic, and hydrologic data sets, without users having to download data. The current operational Giovanni interfaces provide the capability to process a number of important satellite measurements, such as (1) ozone and other trace gases from TOMS, OMI, HALOE, and MLS; (2) air temperature, water vapor, and geopotential height from AIRS; (3) aerosols from MODIS TerrdAqua, and GOCART model; (4) precipitation from TRMM and ground measurements; (5) chlorophyll and other ocean color products from SeaWiFS and MODIS Aqua; and (6) sea surface temperature from MODIS Aqua. Depending on the input data structure, the system provides simple statistical analysis and creates time-averaged area plot, area-averaged time series, animations, Hovmoller latitude vs. time and longitude vs. time plots, as well as vertical profiles. The inter-comparison interfaces allow a user to compare observations from different instruments, to conduct anomaly analysis, and to study basic relationships between physical parameters. Giovanni handles data with different temporal and spatial resolutions and, thus, enables both regional and global long-term climate research and short-term special events investigation, as well as data validations and assessments. Because of its simplicity of usage, Giovanni is powerful and versatile, able to assist a wide range of users, from the discipline scientists conducting preliminary research in various fields, to students in the classroom learning about weather, climate, and other natural phenomena. Giovanni can be accessed from: http://disc. esfc.nasa.gov/techlab/giovanni/index.shtml

Shen, S.↗
NASA NTRS1974

Water survey of Canada: Application for use of ERTS-A for retransmission of water resources data

The author has identified the following significant results. Water resources data including water level, water velocity, precipitation, air temperature, ice condition, DCP battery voltage, and water stage recorder clock operation have been transmitted from remote areas in Canada using the ERTS Data Collection System. The Data Collection Platforms have met all requirements. The suitability of satellite retransmission as a means of obtaining data from remote areas has been demonstrated. The present network of 9 Data Collection Platforms will be expanded to 28 to develop a quasi-operational network.

Halliday, R. A.↗
NASA NTRS2014

Comparing Geologic Data Sets Collected by Planetary Analog Traverses and by Standard Geologic Field Mapping: Desert Rats Data Analysis

Geologic mapping involves interpreting relationships between identifiable units and landforms to understand the formative history of a region. Traditional field techniques are used to accomplish this on Earth. Mapping proves more challenging for other planets, which are studied primarily by orbital remote sensing and, less frequently, by robotic and human surface exploration. Systematic comparative assessments of geologic maps created by traditional mapping versus photogeology together with data from planned traverses are limited. The objective of this project is to produce a geologic map from data collected on the Desert Research and Technology Studies (RATS) 2010 analog mission using Apollo-style traverses in conjunction with remote sensing data. This map is compared with a geologic map produced using standard field techniques.

Feng, Wanda↗
NASA NTRS2018

The Importance of Contamination Knowledge - Insights into Mars Sample Return

The Astromaterials Acquisition and Curation Office at NASA Johnson Space Center (JSC), in Houston, TX (henceforth Curation Office) manages the curation of all past, present, and future extraterrestrial samples returned by NASA missions and shared collections from international partners, preserving their integrity for future scientific study while providing the samples to the international community in a fair and unbiased way. The Curation Office also curates all reference and witness materials for each mission (e.g., flight and non-flight hardware coupons; lubricants; non-flight, flight-like, and flown witness plates). These reference and witness materials provide the scientific community with the fundamental ability to reconstruct the contamination/alteration history of the sample collection through the course of the mission, with the overall goal of strengthening the scientific conclusions drawn from the study of returned materials. The information gained from characterizing the physical, biological, inorganic, and organic chemical properties of reference and witness materials is defined as the Contamination Knowledge (CK) of the sample collection. Unlike the data collected for Contamination Control (CC) and Planetary Protection (PP), CK is exclusively concerned with preserving reference and witness materials for study by future scientists upon sample return. Although CC and PP data collected for sample integrity and forward contamination purposes can be complementary to CK, they are two separate data sets with distinct objectives. A robust collection of samples for CK is necessary to allow the extraterrestrial material in a returned sample to be distinguished from terrestrial contamination. Traditionally CK is utilized by sample scientists in order to accomplish the mission’s scientific objectives, however this information can also be utilized by the Office of Planetary Protection to help evaluate the presence of any back contamination. Mars 2020, the first phase of a potential multipart Mars Sample Return (MSR) campaign, is expected to contribute to NASA’s Mars Exploration Program Science Goals by filling in knowledge gaps concerning: 1) the existence of past or present life on Mars, 2) the past and present climate of Mars, 3) the geology of Mars, and 4) hazards associated with human exploration of Mars. Although there is debate concerning which samples will best answer these questions, the necessity for proper sample blanks is well-understood. The CC and PP requirements, driven by the restricted Class V mission designation, are the most stringent of any sample return mission in recent history. The extremely low levels of allowable terrestrial contamination on the spacecraft and rover can complicate these analyses given the detection limits of current analytical instrumentation, especially in the case of biological contamination. By collecting and curating unanalyzed samples specifically for CK, future sample scientists will not be relegated to: 1) relying on data collected using possibly obsolete tools and techniques for return sample blanks, or 2) using remnants of extracted and/or cultured samples from ATLO (Assembly, Test, and Launch Operations), which could be incompatible with the desired experimental endpoints or state-of-the-art techniques available at the time of sample return.The addition of biological experimental endpoints to a sample return campaign’s objectives broadens the requisite range in preservation environments (e.g. inert ultra-pure nitrogen gaseous environment at 18 degrees Centigrade versus less than or equal to minus 80 degrees Centigrade) and types of CK samples. As a result, the Curation Office will also curate the following CK samples at less than or equal to minus 80 degrees Centigrade for the Mars 2020 mission: 1) unanalyzed swabs and wipes in sterile containers, 2) all recirculation filters from the clean rooms used for sample and caching subsystem assembly and all filters from the laminar flow benches used to assemble sample intimate hardware, and 3) witness plates collecting airborne contamination within the assembly clean rooms. It has been Curation Office policy since the Apollo missions to preserve as many pristine samples as possible for future scientific research. Although CK is required to be collected for all stages of the MSR campaign, the CK for the Mars 2020 mission is the most critical for understanding contamination in the returned samples given the intimacy between the Martian samples and the Mars 2020 flight hardware. This presentation highlights the importance of CK for sample return missions as well as the traditional and novel types of CK samples required for a successful MSR campaign.

Harrington, A. D.↗
NASA NTRS1973

Results of the 1971 Corn Blight Watch experiment.

The objective of the experiment was to evaluate the use of advanced remote sensing techniques to detect the development and spread of southern corn leaf blight during the growing season across the Corn Belt region. The sampling plan involved the selection of the study area, the determination of the flightline, and the determination of a field sample design. Aspects of data acquisition are discussed, giving attention to ground data collection and aerial data collection. Details of data flow are considered along with data analysis procedures and corn blight records. The experiment results are examined, taking into account photointerpretation results, the machine analysis of multispectral scanner data results, the influence of blight on yields, and questions of crop identification.

Macdonald, R. B.↗
NASA NTRS1988

Program Collects And Analyzes Thermoelectric Data

Large gradient seebeck coefficient measurement computer program gathers many channels of data, performs analysis, and plots each set of data simutaneously. User can modify code to alter number of channels of data collected and sampling rate and equations that process data. Written in HP Basic. Program also adaptable to other types of data.

Chmielewski, Art B.↗
NASA NTRSDate not supplied

TOWARD A METHOD FOR SCALING HUMAN BODY MODELS IN AN IMU-BASED WORKFLOW

BACKGROUND Scaled biomechanical models can more accurately inform crew health decisions when tailored to the wide range of astronaut sizes. One component to improve scaling of existing models to better represent each unique astronaut’s size is the individual length scaling of limbs. Traditionally, these lengths are determined by motion capture or manual measurement. A new method is herein proposed for length scaling which can be done by measuring linear and angular accelerations at a desired point during isolated motion around a point of rotation, then calculating the distance between the desired point and point of rotation. When an Inertial Measurement Unit (IMU) device is placed at the distal point of a limb, the isolated motion is about that limb’s proximal joint. For example, to measure forearm length, an IMU is placed at the wrist, the point of rotation is at the elbow, and the isolated motion is forearm flexion and extension. These calculated lengths are then used to scale models to each unique astronaut’s size, thereby improving the applicability of the model. This method of scaling limb segments can be used for any limb that has an easily defined proximal joint for the limb to rotate around including hands, arms, legs, feet. Utilizing IMUs for data collection also provides the synergistic ability to record data without a dedicated space in a room with many cameras, therefore reducing the data collection footprint, or record data where optical motion capture is not possible, such as inside a spacesuit. METHODS AND RESULTS To test this method, upper body data collection was performed with 5 Xsens DOT IMUs on a single subject. IMUs consist of an accelerometer, a gyroscope, and a magnetometer which collect linear acceleration, angular velocity, and magnetic fluctuations, respectively. Before any ground-based laboratory collection, the magnetic fluctuations are used to correct the heading of the IMU in space relative to the Earth’s magnetic field. The direct measurement of angular velocity is integrated to calculate angular acceleration. Then the linear acceleration ( a ) and angular acceleration (α) are solved using r = at/α to calculate the radius, which in this case is the distance between the IMU and the point of rotation (i.e., segment length). The IMU must be placed at the most distal point of the limb being measured (i.e., ankle if measuring lower leg length) and the test plan must consist of an isolated motion about that limb’s proximal joint (i.e., knee flexion and extension if measuring lower leg length). The distances (radii) calculated at every time interval were filtered (bandpass filter keeping 5th-90th percentile data) to eliminate outliers and spurious data that occur when the isolated motion was stopped or nearly stopped. The remaining distances were averaged, resulting in the calculated limb length. Scaling factors were then computed by dividing the calculated limb length by the unscaled model’s length. These scale factors are plugged into the Scale Tool in OpenSim [1,2] to apply the scaling to the OpenSim Full Body Rajagopal Model [3,4]. Manual measurements of limb lengths were taken before data collection started and used for comparing against the calculated lengths. The Anthropometric Survey of US Army Personnel (ANSUR II) [5] was also used as a third source of reference for limb length measurements. The following measurements were retrieved from the subject before data collection: 34.5 cm from L1 to C7 (thorax), 25.7 cm from C7 Joint Center (JC) to head vertex (neck and head), 36.3 cm from shoulder JC to elbow JC (humerus), 29.5 cm from elbow JC to wrist JC (forearm), and 16.2 cm from clavicle to acromion (clavicle). Of those five, forearm and humerus lengths were calculated using this proposed method to obtain preliminary results. The forearm length after filtering and averaging was calculated to be 37.6 cm. This is a 28% overestimation from the measured forearm length (29.5 cm). The humerus length after filtering and averaging was calculated to be 47.8 cm. This is a 31% difference from the measured subject length (36.3 cm). Sources of error include imperfect isolated motion (method currently expects that motion should be perfectly circular in a 2D plane, include no rotation of the IMU, and be relatively smooth; a more secure IMU attachment method will help), unrefined filter techniques (removed highest and lowest values with 20% high and low pass filters and no smoothing filters), arbitrary removal of stopped or near stopped data (kept data for only a short range before and after the angular velocity peaking), and a more representative method for removing gravitational acceleration is needed (current method is to zero all accelerations against a baseline taken just before the isolated motion which does not account for the gravitational acceleration changed due to IMU rotation during movement). Addressing these error sources will improve the accuracy of the limb length calculation. Next steps include creating a method for whole-body scaling estimation using individual limb scale factors. Continued pursuit of these techniques is expected to enable acquiring anthropometric information using only IMUs in real-time.

E. K. Marecki↗
NASA NTRS1992

An on-orbit viewpoint of life sciences research

As a Payload Specialist and a life science researcher, I want to present several issues that impact life science research in space. During early space station operations, life science and other experiments will be conducted in a time-critical manner and there will be the added duties of both space shuttle and space station systems operation (and the concomittent training overhead). Life sciences research is different from other science research done in space because the crew is involved both as an operator and as a subject. There is a need for pre- and post-flight data collection as well as in flight data collection. It is imperative that the life science researcher incorporate the crew members into their team early enough in the training cycle to fully explain the science and to make the crew aware of the importance and sensitivities of the experiment. During the pre-flight phase, the crew is incredibly busy with a myriad of duties. Therefore, it is difficult to get 'pristine' subjects for the baseline data collection. There are also circadian shifts, travel, and late nights to confound the data. During this time it is imperative that the researcher develop, along with the crew, a realistic estimate of crew-time required for their experiment. In flight issues that affect the researcher are the additional activities of the crew, the stresses inherent in space flight, and the difficulty of getting early in-flight data. During SSF activities, the first day or two will be taken up with rendezvous and docking. Other issues are the small number of subjects on any given flight, the importance of complete and concise procedures, and the vagaries of on-board data collection. Post flight, the crew is tired and experiences a 'relaxation.' This along with circadian shifts and rapid re-adaptation to 1-g make immediate post-flight data collection difficult. Finally, the blending of operational medicine and research can result in either competition for resources (crew time, etc.) or influence on the physiological state of the crew. However, the unique opportunity to conduct research in an environment that cannot be duplicated on Earth outweighs the 'challenges' that exist for space life researchers.

Lichtenberg, Byron K.↗
NASA NTRS1994

Software agents for the dissemination of remote terrestrial sensing data

Remote terrestrial sensing (RTS) data is constantly being collected from a variety of space-based and earth-based sensors. The collected data, and especially 'value-added' analyses of the data, are finding growing application for commercial, government, and scientific purposes. The scale of this data collection and analysis is truly enormous; e.g., by 1995, the amount of data available in just one sector, NASA space science, will reach 5 petabytes. Moreover, the amount of data, and the value of analyzing the data, are expected to increase dramatically as new satellites and sensors become available (e.g., NASA's Earth Observing System satellites). Lockheed and other companies are beginning to provide data and analysis commercially. A critical issue for the exploitation of collected data is the dissemination of data and value-added analyses to a diverse and widely distributed customer base. Customers must be able to use their computational environment (eventually the National Information Infrastructure) to obtain timely and complete information, without having to know the details of where the relevant data resides and how it is accessed. Customers must be able to routinely use standard, widely available (and, therefore, low cost) analyses, while also being able to readily create on demand highly customized analyses to make crucial decisions. The diversity of user needs creates a difficult software problem: how can users easily state their needs, while the computational environment assumes the responsibility of finding (or creating) relevant information, and then delivering the results in a form that users understand? A software agent is a self-contained, active software module that contains an explicit representation of its operational knowledge. This explicit representation allows agents to examine their own capabilities in order to modify their goals to meet changing needs and to take advantage of dynamic opportunities. In addition, the explicit representation allows agents to advertize their capabilities and results to other agents, thereby allowing the collection of agents to reuse each others work.

Toomey, Christopher N.↗
NASA NTRS2018

Initial Approach to Collect Small Unmanned Aircraft System Off-Nominal Operational Situations Data

NASA is developing the Unmanned Aircraft System Traffic Management research platform to safely integrate small unmanned aircraft operations in large-scale at low-altitudes. As a part of this effort, small unmanned aircraft system off-nominal operational situations data collection process has been developed to take lessons learned and to reinforce operational compliance. In this paper, descriptions of variables used for digital data collection and an online report form for collection of observational data from the operators (contextual data) are provided. They are used to collect off-nominal data from the Unmanned Aircraft System Traffic Management National Campaign in 2017. The digital data show that 2 out of 118 campaign operations (1.7%) encountered loss of navigation. Since the campaign aircraft used Global Positioning System for navigation, it is likely that unobstructed view of the sky at the campaign locations contributed to this small number. Also, 4 out of 47 operations (8.5%) encountered loss of communications. A relatively short distance between ground control system and aircraft, ranging from 2300 feet to 4200 feet, likely contributed to this small number. There was no data to identify the loss of communications condition, aircraft received signal strength, for the remaining 71 operations suggesting that some operators may not be monitoring unmanned aircraft communications system performance or monitoring it with different parameters. For the contextual data, due to the low number of total reports during the campaign, no significant trends emerged. This is an initial attempt to collect contextual data from small unmanned aircraft operators about off-nominal situations, and changes will be made to the future data collection to improve the amount and quality of the information.

unmanned aviation systems traffic management (UTM)↗
NASA NTRS2018

Initial Approach to Collect Small Unmanned Aircraft System Off-Nominal Operational Situations Data

NASA is developing the Unmanned Aircraft System Traffic Management research platform to safely integrate small unmanned aircraft operations in large-scale at low-altitudes. As a part of this effort, small unmanned aircraft system off-nominal operational situations data collection process has been developed to take lessons learned and to reinforce operational compliance. In this paper, descriptions of variables used for digital data collection and an online report form for collection of observational data from the operators (contextual data) are provided. They are used to collect off-nominal data from the Unmanned Aircraft System Traffic Management National Campaign in 2017. The digital data show that 2 out of 118 campaign operations (1.7%) encountered loss of navigation. Since the campaign aircraft used Global Positioning System for navigation, it is likely that unobstructed view of the sky at the campaign locations contributed to this small number. Also, 4 out of 47 operations (8.5%) encountered loss of communications. A relatively short distance between ground control system and aircraft, ranging from 2300 feet to 4200 feet, likely contributed to this small number. There was no data to identify the loss of communications condition, aircraft received signal strength, for the remaining 71 operations suggesting that some operators may not be monitoring unmanned aircraft communications system performance or monitoring it with different parameters. For the contextual data, due to the low number of total reports during the campaign, no significant trends emerged. This is an initial attempt to collect contextual data from small unmanned aircraft operators about off-nominal situations, and changes will be made to the future data collection to improve the amount and quality of the information.

Jung, Jaewoo↗
NASA NTRS2000

BOREAS TE-9 NSA Canopy Biochemistry

The BOREAS TE-9 team collected several data sets related to chemical and photosynthetic properties of leaves. This data set contains canopy biochemistry data collected in 1994 in the NSA at the YJP, OJR, OBS, UBS, and OA sites, including biochemistry lignin, nitrogen, cellulose, starch, and fiber concentrations. These data were collected to study the spatial and temporal changes in the canopy biochemistry of boreal forest cover types and how a high-resolution radiative transfer model in the mid-infrared could be applied in an effort to obtain better estimates of canopy biochemical properties using remote sensing. The data are available in tabular ASCII files. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Hall, Forrest G.↗
NASA NTRS2004

Evaluation of Experimental Data from the GAINS Balloon GPS Surface Reflection Instrument

The GPS Surface Reflection Instrument was integrated as an experiment on the GAINS (Global Airocean IN-situ System) 48-hour balloon mission flown in September 2001. The data collected by similar instruments in the past has been used to measure sea state from which ocean surface winds can be accurately estimated. The GPS signal has also been shown to be reflected from wetland areas and even from subsurface moisture. The current version of the instrument has been redesigned to be more compact, use less power, and withstand a greater variation in environmental conditions than previous versions. This instrument has also incorporated a new data collection mode to track 5 direct satellites (providing a continuous navigation solution) and multiplex the remaining 7 channels to track the reflected signal of the satellite tracked in channel 0. The new software mode has been shown to increase the signal to noise ratio of the collected data and enhance the science return of the instrument. During the 48-hour flight over the Northwest US, the instrument will measure surface reflections that can be detected over the balloon's ground track. Since ground surface elevations in this area vary widely from the WGS-84 ellipsoid altitude, the instrument software has been modified to incorporate a surface altitude correction based on USGS 30-minute Digital Elevation Models. Information presented will include facts about instrument design goals, data collection methodologies and algorithms, and results of the science data analyses for the 48-hour mission.

Gance, George G.↗
NASA NTRS2002

Evaluation of Experimental Data from the Gains Balloon GPS Surface Reflection Instrument

The GPS Surface Reflection Instrument was integrated as an experiment on the GAINS (Global Airocean IN-situ System) 48-hour balloon mission flown in June 2002. The data collected by similar instruments in the past has been used to measure sea state from which ocean surface winds can be accurately estimated. The GPS signal has also been shown to be reflected from wetland areas and even from subsurface moisture. The current version of the instrument has been redesigned to be more compact, use less power, and withstand a greater variation in environmental conditions than previous versions. This instrument has also incorporated a new data collection mode to track 5 direct satellites (providing a continuous navigation solution) and multiplex the remaining 7 channels to track the reflected signal of the satellite tracked in channel 0. The new software mode has been shown to increase the signal to noise ratio of the collected data and enhance the science return of the instrument. During the GAINS balloon flight over the Northwest US, the instrument measured surface reflections as they were detected over the balloon's ground track. Since ground surface elevations in this area vary widely from the WGS-84 ellipsoid altitude, the instrument software has been modified to incorporate a surface altitude correction based on USGS 30-minute Digital Elevation Models. Information presented will include facts about instrument design goals, data collection methodologies and algorithms, and will focus on results of the science data analyses for the mission.

Ganoe, George G.↗