Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “error rate”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

In-Flight Guidance, Navigation, and Control Performance Results for the GOES-16 Spacecraft

The Geostationary Operational Environmental Satellite-R Series (GOES-R), which launched in November 2016, is the first of the next generation geostationary weather satellites. GOES-R provides 4 times the resolution, 5 times the observation rate, and 3 times the number of spectral bands for Earth observations compared with its predecessor spacecraft. Additionally, Earth relative and Sun-relative pointing and pointing stability requirements are maintained throughout reaction wheel desaturation events and station keeping activities, allowing GOES-R to provide continuous Earth and sun observations. This paper reviews the pointing control, pointing stability, attitude knowledge, and orbit knowledge requirements necessary to realize the ambitious Image Navigation and Registration (INR) objectives of GOES-R. This paper presents a comparison between low-frequency on-orbit pointing results and simulation predictions for both the Earth Pointed Platform (EPP) and Sun Pointed Platform (SPP). Results indicate excellent agreement between simulation predictions and observed on-orbit performance, and compliance with pointing performance requirements. The EPP instrument suite includes 6 seismic accelerometers sampled at 2 KHz, allowing in-flight verification of jitter responses and comparison back to simulation predictions. This paper presents flight results of acceleration, shock response spectrum (SRS), and instrument line of sight responses for various operational scenarios and instrument observation modes. The results demonstrate the effectiveness of the dual-isolation approach employed on GOES-R. The spacecraft provides attitude and rate data to the primary Earth-observing instrument at 100 Hz, which are used to adjust instrument scanning. The data must meet accuracy and latency numbers defined by the Integrated Rate Error (IRE) requirements. This paper discusses the on-orbit IRE results, showing compliance to these requirements with margin. During the spacecraft checkout period, IRE disturbances were observed and subsequently attributed to thermal control of the Inertial Measurement Unit (IMU) mounting interface. Adjustments of IMU thermal control and the resulting improvements in IRE are presented. Orbit knowledge represents the final element of INR performance. Extremely accurate orbital position is achieved by GPS navigation at Geosynchronous Earth Orbit (GEO). On-orbit performance results are shown demonstrating compliance with the stringent orbit position accuracy requirements of GOES-R, including during station keeping activities and momentum desaturation events. As we show in this paper, the on-orbit performance of the GNC design provides the necessary capabilities to achieve GOES-R mission objectives.

Chapel, Jim↗
NASA NTRS2017

Effects of Retinal Eccentricity on Human Manual Control

This study investigated the effects of viewing a primary flight display at different retinal eccentricities on human manual control behavior and performance. Ten participants performed a pitch tracking task while looking at a simplified primary flight display at different horizontal and vertical retinal eccentricities, and with two different controlled dynamics. Tracking performance declined at higher eccentricity angles and participants behaved more nonlinearly. The visual error rate gain increased with eccentricity for single-integrator-like controlled dynamics, but decreased for double-integrator-like dynamics. Participants' visual time delay was up to 100 ms higher at the highest horizontal eccentricity compared to foveal viewing. Overall, vertical eccentricity had a larger impact than horizontal eccentricity on most of the human manual control parameters and performance. Results might be useful in the design of displays and procedures for critical flight conditions such as in an aerodynamic stall.

system identification↗
NASA NTRS2017

UAS Well Clear Recovery Against Non-Cooperative Intruders Using Vertical Maneuvers

This paper documents a study that drove the development of a mathematical expression in the minimum operational performance standards (MOPS) of detect-and-avoid (DAA) systems for unmanned aircraft systems (UAS). This equation describes the conditions under which vertical maneuver guidance could be provided during recovery of well clear separation with a non-cooperative VFR aircraft in addition to horizontal maneuver guidance. Although suppressing vertical maneuver guidance in these situations increased the minimum horizontal separation from 500 to 800 feet, the maximum severity of loss of well clear increased in about 35 of the encounters compared to when a vertical maneuver was preferred and allowed. Additionally, analysis of individual cases led to the identification of a class of encounter where vertical rate error had a large effect on horizontal maneuvers due to the difficulty of making the correct left-right turn decision: crossing conflict with intruder changing altitude. These results supported allowing vertical maneuvers when UAS vertical performance exceeds the relative vertical position and velocity accuracy of the DAA tracker given the current velocity of the UAS and the relative vertical position and velocity estimated by the DAA tracker. Looking ahead, these results indicate a need to improve guidance algorithms by utilizing maneuver stability and near mid-air collision risk when determining maneuver guidance to regain well clear separation.

detect and avoid↗
NASA NTRS2017

Payload Performance of Third Generation TDRS and Future Services

NASA has accepted two of the 3rd generation Tracking and Data Relay Satellites, TDRS K, L, and M, designed and built by Boeing Defense, Space & Security (DSS). TDRS K, L, and M provide S-band Multiple Access (MA) service and S-band, Ku-band and Ka-band Single Access (SA) services to near Earth orbiting satellites. The TDRS KLM satellites offer improved services relative to the 1st generation TDRS spacecraft, such as: an enhanced MA service featuring increased EIRPs and G/T; and Ka-band SA capability which provides a 225 and 650 MHz return service (customer-to-TDRS direction) bandwidth and a 50 MHz forward service (TDRS-to-customer direction) bandwidth. MA services are provided through a 15 element forward phased array that forms up to two beams with onboard active beamforming and a 32 element return phased array supported by ground-based beamforming. SA services are provided through two 4.6m tri-band reflector antennas which support program track pointing and autotrack pointing. Prior to NASAs acceptance of the satellites, payload on-orbit testing was performed on each satellite to determine on-orbit compliance with design requirements. Performance parameters evaluated include: EIRP, G/T, antenna gain patterns, SA antenna autotrack performance, and radiometric tracking performance. On-orbit antenna calibration and pointing optimization was also performed on the MA and SA antennas including 24 hour duration tests to characterize and calibrate out diurnal effects. Bit-Error-Rate (BER) tests were performed to evaluate the end-to-end link BER performance of service through a TDRS K and L spacecraft. The TDRS M is planned to be launched in August 2017. This paper summarizes the results of the TDRS KL communications payload on-orbit performance verification and end-to-end service characterization and compares the results with the performance of the 2nd generation TDRS J. The paper also provides a high-level overview of an optical communications application that will augment the data rates supported by the Space Network.

RF↗
NASA NTRS2017

Payload Performance of TDRS KL and Future Services

NASA has accepted two of the 3nd generation Tracking and Data Relay Satellites, TDRS K, L, and M, designed and built by Boeing Defense, Space Security (DSS). TDRS K, L, and M provide S-band Multiple Access (MA) service and S-band, Ku-band and Ka-band Single Access (SA) services to near Earth orbiting satellites. The TDRS KLM satellites offer improved services relative to the 1st generation TDRS spacecraft, such as: an enhanced MA service featuring increased EIRPs and GT; and Ka-band SA capability which provides a 225 and 650 MHz return service (customer-to-TDRS direction) bandwidth and a 50 MHz forward service (TDRS-to-customer direction) bandwidth. MA services are provided through a 15 element forward phased array that forms up to two beams with onboard active beamforming and a 32 element return phased array supported by ground-based beamforming. SA services are provided through two 4.6m tri-band reflector antennas which support program track pointing and autotrack pointing. Prior to NASAs acceptance of the satellites, payload on-orbit testing was performed on each satellite to determine on-orbit compliance with design requirements. Performance parameters evaluated include: EIRP, GT, antenna gain patterns, SA antenna autotrack performance, and radiometric tracking performance. On-orbit antenna calibration and pointing optimization was also performed on the MA and SA antennas including 24 hour duration tests to characterize and calibrate out diurnal effects. Bit-Error-Rate (BER) tests were performed to evaluate the end-to-end link BER performance of service through a TDRS K and L spacecraft. The TDRS M is planned to be launched in August 2017. This paper summarizes the results of the TDRS KL communications payload on-orbit performance verification and end-to-end service characterization and compares the results with the performance of the 2nd generation TDRS J. The paper also provides a high-level overview of an optical communications application that will augment the data rates supported by the Space Network.

Laser↗
NASA NTRS2018

Performance of Variable Coded Modulations over a Nonlinear Channel for VCM Protocol Red Book

This presentation provides a summary of the results obtained from a study which evaluates the performance of variable coded modulations specified in the "Variable Coded Modulation Protocol" CCSDS Red Book, over a nonlinear channel that is currently on the CCSDS Blue Book track. The objectives are to perform simulation that identifies the operating signal-to-noise-power ratio required to achieve a codeword error rate of 1e-4 over the specified nonlinear channel for various modulations (i.e. BPSK, QPSK, 8-PSK) and LDPC coding schemes, and compare against performance over an ideal additive white Gaussian channel. We select a only subset of operating modes to perform the analysis which are based on a number of mitigation techniques to combat the nonlinear distortions. Specifically, transmitter centroidal pre-distortion, phase post-distortion and receiver mean phase estimation are analyzed in this study.

coding↗
NASA NTRS2018

Delay Tolerant Network Routing as a Machine Learning Classification Problem

This paper discusses a machine learning-based approach to routing for delay tolerant networks (DTNs) [1]. DTNs are networks which experience frequent disconnections between nodes, uncertainty of an end-to-end path, long one-way trip times, and may have high error rates and asymmetric links. Such networks exist in deep space satellite networks, very rural environments, disaster areas and underwater environments. In this work, we use machine learning classifiers to predict a set of neighboring nodes which are the most likely to deliver a message to a desired location based on message history delivery information.We use the Common Open Research Emulator (CORE) [2] to emulate the DTN environment based on real-world location traces and collect network traffic statistics from the Bundle Protocol implementation IBR-DTN [3]. The software architecture for classification-based routing, analysis and preparation of the network history data and prediction results are discussed.

Delay Tolerant Networks↗
NASA NTRS2019

In-Flight Line-Of-Sight Pointing Performance for the GOES-16 and GOES-17 Spacecraft

The Geostationary Operational Environmental Satellite-R program (GOES-R) has launched two of the next generation geostationary weather satellites, both of which are now fully operational. GOES-16 launched in November 2016, and GOES-17 launched in March 2017. In this paper, we present the pointing and pointing stability results of the two spacecraft, with specific focus on aspects of the design related to mitigating jitter. The flight instrument suite includes 6 seismic accelerometers sampled at approximately 2 kilohertz, allowing in-flight verification of pointing stability and comparison back to simulation predictions. This paper compares the observed flight results with the simulation predictions for acceleration and shock response spectrum (SRS) for various operational scenarios and instrument observation modes. Passive isolation of both the reaction wheels and the payload deck have proved to be effective in reducing jitter responses. Active Vibration Damping (AVD) of flexible-body modes attenuates the low frequency motion of the vehicle appendages, improving the low-frequency pointing performance. Knowledge of the instrument scan mirror motion is fed forward to the reaction wheel control, reducing disturbances on the spacecraft bus. Attitude knowledge and rate data are provided to the primary Earth-observing instrument with an accuracy defined by the Integrated Rate Error (IRE) requirements. The data are used to adjust instrument scanning. As we show in this paper, the in-flight performance of the GN&C (Guidance, Navigation and Control) design provides the necessary capabilities to achieve the demanding GOES-R mission objectives while its robustness enabled the simultaneous operation of the Advanced Baseline Imager (ABI) prime and redundant cryocoolers (CCs) to resolve an in-flight cooling anomaly on GOES-17.

Line-of-Sight↗
NASA NTRS2019

Application of Machine Learning Techniques to Delay Tolerant Network Routing

This dissertation discusses several machine learning techniques to improve routing in delay tolerant networks (DTNs). These are networks in which there may be long one-way trip times, asymmetric links, high error rates, and deterministic as well as non-deterministic loss of contact between network nodes, such as interplanetary satellite networks, mobile ad hoc networks and wireless sensor networks. This work uses historical network statistics to train a multi-label classifier to predict reliable paths through the network. In addition, a clustering technique is used to predict future mobile node locations. Both of these techniques are used to reduce the consumption of resources such as network bandwidth, memory and data storage that is required by replication routing methods often used in opportunistic DTN environments. Thesis contributions include: an emulation tool chain developed to create a DTN test bed for machine learning, the network and software architecture for a machine learning based routing method, the development and implementation of classification and clustering techniques and performance evaluation in terms of machine learning and routing metrics.

Dudukovich, Rachel M.↗
NASA NTRS2016

Reliability Characterization of TaOx-Based Commercial ReRAM in Combination with Radiation

We present reliability data combined with total dose gamma radiation for one of the first commercially available resistive memory devices. These Tantalum Oxide (TaOX)-based resistive memory chips demonstrate operation in dynamic program and erase testing up to ~130 Krad(Si) of 60Co gamma dose. In static and unbiased conditions, the stored data in the memory cells were able to withstand up to 50Mrad(Si) of exposure. The access circuitry, though, seemed less robust to gamma radiation and was able to operate only up to a total dose of 3Mrad(Si). Post exposure reliability as indicated by endurance, cycling error rate, and data retention tests showed no detectable impact from the combination with prior gamma irradiation. Overall, the total dose radiation tolerance of the commercial TaOx-based resistive memory chip appears to be higher than flash memory chips and in agreement with prior tests conducted with single cell resistive memories.

total ionizing dose↗
NASA NTRS2015

Measuring and Modeling Shared Visual Attention

Multi-person teams are sometimes responsible for critical tasks, such as flying an airliner. Here we present a method using gaze tracking data to assess shared visual attention, a term we use to describe the situation where team members are attending to a common set of elements in the environment. Gaze data are quantized with respect to a set of N areas of interest (AOIs); these are then used to construct a time series of N dimensional vectors, with each vector component representing one of the AOIs, all set to 0 except for the component corresponding to the currently fixated AOI, which is set to 1. The resulting sequence of vectors can be averaged in time, with the result that each vector component represents the proportion of time that the corresponding AOI was fixated within the given time interval.We present two methods for comparing sequences of this sort, one based on computing the time varying correlation of the averaged vectors, and another based on a chi-square test testing the hypothesis that the observed gaze proportions are drawn from identical probability distributions.We have evaluated the method using synthetic data sets, in which the behavior was modeled as a series of activities, each of which was modeled as a first-order Markov process. By tabulating distributions for pairs of identical and disparate activities, we are able to perform a receiver operating characteristic (ROC) analysis, allowing us to choose appropriate criteria and estimate error rates. Using these criteria, we have applied the methods to data from airline crews, collected in a high-fidelity flight simulator (Gontar Hoermann, 2014). We conclude by considering the problem of automatic (blind) discovery of activities, using methods developed for text analysis.

Mulligan, Jeffrey B.↗
NASA NTRSDate not supplied

Controls Algorithms, Models, and Stability Assessments of the RCS and TVC systems on Mars Ascent Vehicle

This paper presents a control systems overview of the Mars Ascent Vehicle (MAV) control design and stability analysis with two separate control methods: Thrust Vector Control (TVC) based control using main engine thrust and Reaction Control System (RCS) via thrusters. A pole-placement TVC controller is proposed to address quickly peaking thrust produced by the MAV solid propulsion engine. The controllerutilizes real-time parameter estimation to calculate control gains using an online pole-placement method. The pole-placement technique allows the controller to maintain constant stability margins throughout the flight under changing parameters and rapidly peaking thrust. A mathematical stability proof via Lyapunov inequality and Nichols method is demonstrated to support the stability of the method. In addition to the TVC control, a phase-plane based RCS control logic is applied to the vehicle for roll control during ascent and all axes during coast phases of flight. The logic implemented is an on-off type logic that applies pre-determined thrusters firings in reference to boundary parameters of pointing and rate error chosen to balance desired pointing with stability. A describing function methodology is applied to the non-linear phase plane loop response to determine linear stability across all flight phases. The controller additionally applies command alteration logic to output signals to account for RCS hardware limitations. The following paper will provide the methodology for controller implementation of the TVC and RCS, and provide a summary of results of the MAV performance applying the aforementioned control design.

Han Woong Bae↗
NASA NTRS2006

Coherent optical array receiver experiment : design, implementation and BER performance of a multichannel coherent optical receiver for PPM signals under atmospheric turbulence

The performance of a coherent free-space optical communication system operating in the presence of turbulence is investigated. Maximum Likelihood Detection techniques are employed to optimally detect Pulse Position Modulated signals with a focal-plane detector array, and reconstruct the turbulence-degraded signals. The experimental demonstration of this project and results may be divided in three parts; two of which have already been explained in previous publications (1,2). This latest paper shows the final experimental results, including investigation of performance of the Coherent Optical Receiver Experiment (CORE) performed at the laboratory facilities at JPL. Bit Error Rate (BER) is presented for single and multichannel optical receivers, where quasi-shot noise limited performance is achieved, under simulated turbulence conditions using non-coherent post-detection processing techniques.

Hassibi, Babak↗
NASA NTRS1998

Experiment Concepts in The Trans-Pacific HDR Satcom Experiment - Phase 2

This paper describes experiment concepts for the Phase-2 of the Trans-Pacific HDR Satcom Experiment (Astronomy). Broadband Satellites serve as a key link in establising a worldwide network of networks, while imposing upon us the particular charcteristics of propagation delay, bandwidth, and error rates which differ from those of terrestrial networks.

Trans-Pacific↗
NASA NTRS2019

Statistical optical link budget analysis

In this paper, we describe work on extending statistical analysis methods to optical communications links, with a primary focus on intensity modulated, direct detected photon-counting channel utilizing pulse-position-modulation (PPM). We performed analysis on the relationship between bit error rate (BER) requirement, statistical characteristics of the received signal power and noise power, and the coded performance curves. We presented link analysis results with preliminary uncertainty quantifications of signal power and noise power. We used the Consultative Committee for Space Data Systems (CCSDS) Serially Concatenated convolutionally coded Pulse Position Modulation (SCPPM) prototype software [1] to obtain coded performance curves under different operating conditions with varying signal power, background noise power, code rates,and PPM modulation orders. Comparison with traditional, deterministic analysis shows that extra margin needs to be reserved to compensate for the performance losses caused by uncertainties of the link parameters.

Cheung, Kar-Ming↗
NASA NTRSDate not supplied

Inverse Text Normalization of Air Traffic Control System Command Center Planning Telecon Transcriptions

We present a hybrid neural network and rule-based Inverse Text Normalization (ITN) method for domains containing unique technical phraseology, specifically ATCSCC planning telecon audio transcriptions. The Air Traffic Control System Command Center (ATCSCC) hosts bihourly planning telephone conferences (or planning telecons) to ensure smooth operations within the National Airspace (NAS). Access to both live and post meeting transcripts of this speech audio would enable quick review of meetings. ITN is the process of converting un-formatted "raw'' speech-to-text transcripts into a human (expert) readable written form. Our hybrid ITN framework utilizes a neural network to format conversational English, and rule-based methods to format domain-specific aviation text. With a preliminary overall Word Error Rate with Punctuation and Capitalization (WER PC) of 8.26, we show that this method has vast potential in being applied to ATCSCC planning telecon audio and other audio/text based data available in ATM.

Air Traffic Management↗
NASA NTRSDate not supplied

Towards Understanding Data Requirements for Developing Automatic Speech Recognition Systems for Air Traffic Control

In recent years, the application of automatic speech recognition has gained popularity across diverse industries, including aviation. Given the many applications focusing on transcribing air traffic control and management communication, this paper explores the training of OpenAI's Whisper model across multiple existing public and private air traffic control voice datasets in an effort to improve robustness. Combining roughly 60+ hours of various air traffic datasets, our goal is to train a unified Whisper model and expect an average word error rate reduction across testing datasets. Furthermore, this work aims to understand the data quantity requirements for achieving state-of-the art results by comprehensively training Whisper on varying dataset sizes. This work has the potential to improve automatic speech recognition performance across the domain, improve understanding of the quantity of data required by an aviation speech recognition system, and lastly provide metrics to compare and improve upon in future research.

ATC↗
NASA NTRS2026

Machine Learning for Predicting Team Functioning in HERA Missions

Team functioning is integral to success in future long term space exploration missions. Proactively detecting declines in team functioning can mitigate conflict and ensure mission success. This project developed a speech-based artificial intelligence (AI) system that unobtrusively predicts degradation in team functioning, including performance and cohesion, in the Human Exploration Research Analog (HERA) Campaigns 4 and 5. The AI system conducted automated analysis of the prosodic (tone of voice) and linguistic (language content) components of speech, modeling interpersonal dynamics at both the turn-taking and day-wide levels. We investigated team functioning via observing structured interactions (i.e., multi-mission space exploration vehicle-extra vehicular activity [MMSEV-EVA], team interaction battery [TIB]) and unstructured interactions before the MMSEV-EVA task. We developed machine learning models to predict team functioning (objective task accuracy, self reported team efficacy and self reported team cohesion) by analyzing OpenSmile acoustic features, linguistic descriptors extracted via the linguistic inquiry and word count (LIWC) dictionary, and semantic embeddings. In the TIB, static models using logistic regression and random forests were not able to predict task accuracy, but predicted team efficacy and cohesion during both the decision making and relational tasks to a moderate level (60-70%). Majority voting on the individual turns to predict day long team efficacy further increased accuracies (70-80%). Finally, long short-term memory (LSTM) models showed the best performance across all variables (80-91%), including task performance. In the MMSEV-EVA, static models achieved an accuracy of 60% with majority voting, which increased to 80% through the incorporation of mission day as a variable, accounting for the learning effect. A key finding across both tasks was the "team-dependent" nature of these interactions; models achieved much higher accuracy when trained on prior days of the same team's data rather than attempting to generalize across entirely different teams, with even 1-2 days of prior data per team achieving 5-15% improvement over team-independent models. In addition, the incorporation of pre-task data from the same team also improves model performance, e.g., incorporating data from the decision-making task of the TIB, which preceded the relational task, improved the prediction of team efficacy and cohesion during the latter. We compared model performance when trained on machine-generated data compared to data that had been further corrected by human annotators. Overall, models trained on human-corrected data exhibited a modest improvement in performance, particularly when acoustic features were used. We found no significant correlation between word error rate (WER) and model accuracy (r(55) = -0.08, p = 0.51), but model’s accuracy was significantly higher for medium/high quality transcription (0.74 (SD = 0.48)) compared to the low-quality group (0.64 (SD = 0.36)) (t(63)=2.82, p = 0.006). Based on these, several design recommendation emerge, that could inform Standards at NASA. Models predicting team functioning should incorporate at least one to two days of historical interaction data, include brief pre-task discussions, and explicitly model temporal learning effects, especially for longer operational tasks. Minimum quality standards for automated speech-processing pipelines are needed, given the performance gains observed with manually corrected acoustic data. Finally, systems should leverage both acoustic features and language embeddings in complementary ways, with modality choices and fusion strategies tailored to mission context, task demands, and data quality requirements.

Shrivatsa Mishra↗