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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.

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At least 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

Coded multiple chirp spread spectrum system and overlay service

An asynchronous spread-spectrum system called coded multiple chirp is proposed, and the possible spread-spectrum overlay over an analog FM-TV signal is investigated by computer simulation. Multiple single-sloped up and down chirps are encoded by a pseudonoise code and decoded by dechirpers (pulse-compression filters) followed by a digital code correlator. The performance of the proposed system, expressed in terms of in probability of bit error and code miss probability, is similar to that of FSK (frequency shift keying) using codewords if sufficient compression gain is used. When chirp is used to overlay an FM-TV channel, two chirp signals with data rate up to 25 kb/s could be overlaid in a 36-MHz satellite transponder without significant mutual interference. Performance estimates for a VSAT (very small aperture terminal) earth station operating at C-band show that a 2.4-m antenna and 300-mW transmitter could send a 2.4-kb/s signal to a large central earth station over an occupied channel.

Kim, Junghwan↗
NASA NTRS1994

GPS tracking of TOPEX/POSEIDON: Results and implications

A reduced dynamic filtering strategy that exploits the unique geometric strength of the Global Positioning System (GPS) to minimize the effects of force model errors has yielded orbit solutions for TOPEX/POSEIDON which appear accurate to better than 3 cm (1 sigma) in the radial component. Reduction of model error also reduces the geographic correlation of the orbit error. With a traditional dynamic approach, GPS yields radial orbit accuracies of 4-5 cm, comparable to the accuracy delivered by satellite laser ranging and the Doppler orbitography and radio positioning integrated by satellite (DORIS) tracking system. A portion of the dynamic orbit error is in the Joint Gravity Model-2 (JGM-2); GPS data from TOPEX/POSEIDON can readily reveal that error and have been used to improve the gravity model.

Bertiger, W. I.↗
NASA NTRS2001

Calibration of of Sun Photometers and Sky Radiance Sensors

The main source of error in retrieving aerosol optical thicknesses using sun photometry comes from the determination of the TOA voltages. The degradation of interference filters is the most important source of the long-term changes in the cross-calibrations. Although major improvements have been made in the design of the filters (interference filters fabricated using ion-assisted deposition), the filters remain the principal factor limiting performance of the sun photometers. Degradation of filters necessitates frequent calibration of sun photometers and frequent measurements of the filter transmission or the relative system response. The degradation of the filters mounted on the CIMEL sun photometers have been monitored since 1993 by the Aerosol Robotic Network (AERONET) project. The decay reported by Holben et al. for the first two years of a CIMEL#s operation is between 1 and 5%. Nevertheless, the filters mounted on CIMEL instruments are regularly replaced after two years of use. The cross-calibration technique consists of taking measurements concurrently with the uncalibrated and the reference sun photometers. While analyzing measurements, the quality of the calibration has to be checked, using the following considerations: (1) any cirrus clouds suspected to be masking the sun, during the calibration period, need to be reported and the corresponding data set removed; and (2) the stability of the day needs to be checked. This chapter will describe calibration techniques, facilities, and protocols used for calibrating sun photometers and sky radiometers.

Pietras, Christophe↗
NASA NTRS2010

Prospects for Habitable World Detections Using James Webb Space Telescope (JWST)

Doppler and transit surveys are finding extrasolar planets of ever smaller mass and radius, and are now sampling the domain of superEarths. Recent results from the Doppler surveys suggest that discovery of a transiting superEarth in the habitable zone of a lower main sequence star may be possible. We evaluate the prospects for an all-sky transit survey targeted to the brightest stars I that would find the most favorable cases for photometric and spectroscopic characterization using the James Webb Space Telescope. We use the proposed Transiting Exoplanet Survey Satellite (TESS) as representative of an all-sky survey. We couple the simulated TESS yield to a sensitivity model for the MIRI and NIRSpec instruments on JWST. Our sensitivity model includes all currently known and anticipated sources of random and systematic error for these instruments. We focus on the TESS planets with radii between Earth and Neptune. Our simulations consider secondary eclipse filter photometry using JWST/MIRI, comparing the 11- and 15- micron bands to measure carbon dioxide absorption in superEarths, as well as JWST!NIRSpec spectroscopy of water absorption from 1.7-3.0 microns, and carbon dioxide absorption at 4.3 microns. We find that JWST will be capable of characterizing dozens of TESS superEarths with temperatures above the habitable range, using both MIRI and NIRspec. We project that TESS will discover about eight nearby habitable transiting superEarths, all orbiting lower main sequence stars. The principal sources of uncertainty in the prospects for JWST characterization of habitable superEarths are superEarth frequency and the nature of superEarth atmospheres. Based on our estimates of these uncertainties, we project that JWST will be able to measure the temperature, and identify molecular absorptions (water, carbon dioxide) in one to four nearby habitable TESS superEarths orbiting lower main sequence stars.

Deming, Drake↗
NASA NTRS1994

Time transfer using geostationary satellites: Implementation of a Kalman filter

Since 1988, various experiments have shown that the TV signals transmitted by direct TV satellites may easily be used to perform time transfers at the level of a few tens of nanoseconds, the main source of error being the uncertainty on the satellite position. We first present the two methods used in our experiment to reduce the effects of the satellite residual motion: the first one consists in estimating the longitude variations of the satellite and then using this information to improve other measurements. This allows reducing the uncertainty to values between 9 and 50 nanoseconds according to the position of the involved stations. In the second method we determine the satellite position by using the data collected by three calibrated stations. Time transfer between each of these stations and a fourth one has been shown to be achievable at the precision level of ten nanoseconds. A new approach based on the use of a Kalman filter is proposed in order to take into account the dynamics of the geostationary satellite. The precisions on orbital elements and clock differences and rates determination given by the first simulated applications of the Kalman filter are presented and compared to those obtained by the other methods.

Meyer, F.↗
NASA NTRS2013

Simultaneous Estimation of Model State Variables and Observation and Forecast Biases Using a Two-Stage Hybrid Kalman Filter

In this paper, we present a two-stage hybrid Kalman filter to estimate both observation and forecast bias in hydrologic models, in addition to state variables. The biases are estimated using the discrete Kalman filter, and the state variables using the ensemble Kalman filter. A key issue in this multi-component assimilation scheme is the exact partitioning of the difference between observation and forecasts into state, forecast bias and observation bias updates. Here, the error covariances of the forecast bias and the unbiased states are calculated as constant fractions of the biased state error covariance, and the observation bias error covariance is a function of the observation prediction error covariance. In a series of synthetic experiments, focusing on the assimilation of discharge into a rainfall-runoff model, it is shown that both static and dynamic observation and forecast biases can be successfully estimated. The results indicate a strong improvement in the estimation of the state variables and resulting discharge as opposed to the use of a bias-unaware ensemble Kalman filter. Furthermore, minimal code modification in existing data assimilation software is needed to implement the method. The results suggest that a better performance of data assimilation methods should be possible if both forecast and observation biases are taken into account.

Data Assimilation↗
NASA NTRS1988

Modal identification using single-mode projection filters and comparison with ERA and MLE results

The Single-Mode Projection Filter (SPF) is a newly developed algorithm for eigensystem parameter identification from both analytical results and test data. The SPF is formulated with a single mode only and practical for parallel processing implementation. Explicit formulations of SPF are derived for the multi-input multi-output (MIMO) system by using the orthogonal matrices of the controllability and observability matrices in the general sense. The modal parameters of SPF are initially obtained from an analytical model in modal space. The experimental data are then processed through SPF to update its modal parameters and to minimize a cost function defined by the norm of an error matrix. The updated modal parameters represent the characteristics of the test data. A two-dimensional global minimum optimization algorithm is developed and applied for the filter update by using the interval analysis method. The SPF is developed based on a single-mode subsystem and identifies only one modal frequency and one modal damping within a specified region. For an n-modes structure, n SPF can be implemented for parallel processing to reduce the computational burden. The SPF is applied to analyze the simulated data for the MAST beam structure. The estimated modal parameters are comparable to those from the Eigensystem Realization Algorithm (ERA) and repeated modal frequencies are identified. The modal analysis of the Spacecraft Control Laboratory Experiment (SCOLE) data is also performed by using the ERA and the Maximum Likelihood Estimate (MLE). The result shows that the first five modal frequencies are very close from ERA and MLE. However, there are slight disparities in the damping rates and the computational burdens are quite different among these two algorithms.

Huang, Jen-Kuang↗
NASA NTRS2006

Development Tests of a Cryogenic Filter Wheel Assembly for the NIRCam Instrument

The James Webb Space Telescope is an infrared-optimized space telescope scheduled for launch in 201 3. Its 6.5-m diameter primary mirror will collect light from some of the first galaxies formed after the big bang. The Near Infrared camera (NIRCam) will detect the first light from these galaxies, provide the necessary tools for studying the formation of stars, aid in discovering planets around other stars, and adjust the wave front error on the primary mirror (Fig. 1). The instrument and its complement of mechanisms and optics will operate at a cryogenic temperature of 35 K. This paper describes tests and test results of the NIRCam Filter Wheel assembly prototype.

McCully, Sean↗
NASA NTRS1991

Geodesy by radio interferometry - Water vapor radiometry for estimation of the wet delay

An important source of error in VLBI estimates of baseline length is unmodeled variations of the refractivity of the neutral atmosphere along the propagation path of the radio signals. This paper presents and discusses the method of using data from a water vapor radiomete (WVR) to correct for the propagation delay caused by atmospheric water vapor, the major cause of these variations. Data from different WVRs are compared with estimated propagation delays obtained by Kalman filtering of the VLBI data themselves. The consequences of using either WVR data or Kalman filtering to correct for atmospheric propagation delay at the Onsala VLBI site are investigated by studying the repeatability of estimated baseline lengths from Onsala to several other sites. The repeatability obtained for baseline length estimates shows that the methods of water vapor radiometry and Kalman filtering offer comparable accuracies when applied to VLBI observations obtained in the climate of the Swedish west coast. For the most frequently measured baseline in this study, the use of WVR data yielded a 13 percent smaller weighted-root-mean-square (WRMS) scatter of the baseline length estimates compared to the use of a Kalman filter. It is also clear that the 'best' minimum elevationi angle for VLBI observations depends on the accuracy of the determinations of the total propagation delay to be used, since the error in this delay increases with increasing air mass.

Elgered, G.↗
NASA NTRS1999

A Polarimeter for SOFIA: Summary of Research

The purpose of this research was to study designs for a far-infrared polarimeter for SOFIA that would greatly surpass the performance of the earlier polarimeter, Stokes, used on the Kuiper Airborne Observatory. Specifically we wished to gain the sensitivity to observe much fainter objects, to provide a choice of passbands, to reduce systematic errors, and to improve the efficiency. All of these objectives were successfully addressed. The gain in sensitivity will be achieved in part by the superior capabilities of SOFIA but to an even greater extent by the incorporation of new-technology detector arrays. We are developing superconducting transition-edge detectors using the "pop-up" design conceived by Dr. Harvey Moseley. The choice of passbands is achieved by providing three alternative optical paths, each with its own spectral filter, half-wave plate, and pupil tens. A new investigation has shown that multiwavelength observations provide an essential feature of far-infrared polarimetry. The principal source of systematic errors in observations of extended objects has been unknown polarization in the reference beams. We have developed a strategy for estimating these errors.

Hildebrand, Roger H.↗
DOE OSTI2020

Towards real-time monitoring: data assimilated time-lapse full waveform inversion for seismic velocity and uncertainty estimation

SUMMARY Rapid development of time-lapse seismic monitoring instrumentations has made it possible to collect dense time-lapse data for tomographically retrieving time-lapse (even continuous) images of subsurface changes. While traditional time-lapse full waveform inversion (TLFWI) algorithms are designed for sparse time-lapse surveys, they lack of effective temporal constraint on time-lapse data, and, more importantly, lack of the uncertainty estimation of the TLFWI results that is critical for further interpretation. Here, we propose a new data assimilation TLFWI method, using hierarchical matrix powered extended Kalman filter (HiEKF) to quantify the image uncertainty. Compared to existing Kalman filter algorithms, HiEKF allows to store and update a data-sparse representation of the cross-covariance matrices and propagate model errors without expensive operations involving covariance matrices. Hence, HiEKF is computationally efficient and applicable to 3-D TLFWI problems. Then, we reformulate TLFWI in the framework of HiEKF (termed hereafter as TLFWI-HiEKF) to predict time-lapse images of subsurface spatiotemporal velocity changes and simultaneously quantify the uncertainty of the inverted velocity changes over time. We demonstrate the validity and applicability of TLFWI–HiEKF with two realistic CO2 monitoring models derived from Frio-II and Cranfield CO2 injection sites, respectively. In both 2-D and 3-D examples, the inverted high-resolution time-lapse velocity results clearly reveal a continuous velocity reduction due to the injection of CO2. Moreover, the accuracy of the model is increasing over time by assimilating more time-lapse data while the standard deviation is decreasing over lapsed time. We expect TLFWI-HiEKF to be equipped with real-time seismic monitoring systems for continuously imaging the distribution of subsurface gas and fluids in the future large-scale CO2 sequestration experiments and reservoir management.

58 GEOSCIENCES↗
DOE OSTI2025

Absolute timing calibration of the Resolve microcalorimeter spectrometer on the X-ray Imaging and Spectroscopy Mission

The Resolve microcalorimeter spectrometer on the X-ray Imaging and Spectroscopy Mission (XRISM) is designed to have a good timing capability with the mission-level requirement of 1 ms as the absolute time tagging accuracy to suffice the needs for observatory science. In the ground calibration campaign, the absolute and relative timing offsets were measured using pulsed X-rays from the modulated X-ray sources. These offsets were used to determine calibration parameters, the Resolve timing coefficients, which are used in the offline correction of event times. In the orbit, reevaluation of the timing coefficients was carried out using the Crab pulsar, which was observed in two periods, one in the performance verification phase and the other in the guest observation phase. We report the absolute timing calibration of XRISM/Resolve using the ground and in-orbit data. Although the requirement is likely satisfied with the ground parameters, the timing coefficients have been refined using the in-orbit calibration to improve the timing accuracy. In addition, for the first time, we present the interpretation of the absolute timing offset originating from the analog and digital processing of X-ray events unique to a microcalorimeter spectrometer and present a complete view of the timing error of the Resolve instrument.

Astronomy and AstroPhysics↗
NASA NTRS1972

Bounding filter - A simple solution to lack of exact a priori statistics.

Wiener and Kalman-Bucy estimation problems assume that models describing the signal and noise stochastic processes are exactly known. When this modeling information, i.e., the signal and noise spectral densities for Wiener filter and the signal and noise dynamic system and disturbing noise representations for Kalman-Bucy filtering, is inexactly known, then the filter's performance is suboptimal and may even exhibit apparent divergence. In this paper a system is designed whereby the actual estimation error covariance is bounded by the covariance calculated by the estimator. Therefore, the estimator obtains a bound on the actual error covariance which is not available, and also prevents its apparent divergence.

Nahi, N. E.↗
NASA NTRS1975

New method for propagating the square root covariance matrix in triangular form

A method proposed by Potter of applying the Kalman-Bucy filter to the problem of estimating the state of a dynamic system is described, in which the square root of the state error covariance matrix is used to process the observations. A new technique which propagates the covariance square root matrix in lower triangular form is given for the discrete observation case. The technique is faster than previously proposed algorithms and is well-adapted for use with the Carlson square root measurement algorithm.

Choe, C. Y.↗
NASA NTRS1981

Algorithms for onboard orbit estimation with Tracking and Data Relay Satellite System data

An investigation is carried out to determine an appropriate estimation technique for onboard orbit determination using simulated Tracking and Data Relay Satellite System (TDRSS) data. Results are presented from studies done using three estimation techniques: an extended Kalman filter, a consider filter, and a sliding batch differential corrector. These estimators are evaluated when used with both baseline and worst-case TDRSS measurement errors and with tracking configurations for two types of orbits: a high-inclination, near-circular orbit with an altitude of 700 km and a moderately inclined, lower altitude orbit. Each estimation result is evaluated by comparing the true with the estimated ephemeris.

Dunham, J. B.↗
NASA NTRS1982

Real time estimation and prediction of ship motions using Kalman filtering techniques

A landing scheme for landing V/STOL aircraft on rolling ships was sought using computerized simulations. The equations of motion as derived from hydrodynamics, their form and the physical mechanisms involved and the general form of the approximation are discussed. The modeling of the sea is discussed. The derivation of the state-space equations for the DD-963 destroyer is described. Kalman filter studies are presented and the influence of the various parameters is assessed. The effect of various modeling parameters on the rms error is assessed and simplifying conclusions are drawn. An upper bound for prediction time of about five seconds is established, with the exception of roll, which can be predicted up to ten seconds ahead.

Triantafyllou, M. A.↗
NASA NTRS1990

Considerations of digital phase modulation for narrowband satellite mobile communication

The Inmarsat-M system for mobile satellite communication is specified as a frequency division multiple access (FDMA) system, applying Offset Quadrature Phase Shift Keying (QPSK) for transmitting 8 kbit/sec in 10 kHz user channel bandwidth. We consider Digital Phase Modulation (DPM) as an alternative modulation format for INMARSAT-M. DPM is similar to Continuous Phase Modulation (CPM) except that DPM has a finite memory in the premodular filter with a continuous varying modulation index. It is shown that DPM with 64 states in the VA obtains a lower bit error rate (BER). Results for a 5 kHz system, with the same 8 kbit/sec transmitted bitstream, is also presented.

Grythe, Knut↗
NASA NTRS2010

Prediction Activities at NASA's Global Modeling and Assimilation Office

The Global Modeling and Assimilation Office (GMAO) is a core NASA resource for the development and use of satellite observations through the integrating tools of models and assimilation systems. Global ocean, atmosphere and land surface models are developed as components of assimilation and forecast systems that are used for addressing the weather and climate research questions identified in NASA's science mission. In fact, the GMAO is actively engaged in addressing one of NASA's science mission s key questions concerning how well transient climate variations can be understood and predicted. At weather time scales the GMAO is developing ultra-high resolution global climate models capable of resolving high impact weather systems such as hurricanes. The ability to resolve the detailed characteristics of weather systems within a global framework greatly facilitates addressing fundamental questions concerning the link between weather and climate variability. At sub-seasonal time scales, the GMAO is engaged in research and development to improve the use of land information (especially soil moisture), and in the improved representation and initialization of various sub-seasonal atmospheric variability (such as the MJO) that evolves on time scales longer than weather and involves exchanges with both the land and ocean The GMAO has a long history of development for advancing the seasonal-to-interannual (S-I) prediction problem using an older version of the coupled atmosphere-ocean general circulation model (AOGCM). This includes the development of an Ensemble Kalman Filter (EnKF) to facilitate the multivariate assimilation of ocean surface altimetry, and an EnKF developed for the highly inhomogeneous nature of the errors in land surface models, as well as the multivariate assimilation needed to take advantage of surface soil moisture and snow observations. The importance of decadal variability, especially that associated with long-term droughts is well recognized by the climate community. An improved understanding of the nature of decadal variability and its predictability has important implications for efforts to assess the impacts of global change in the coming decades. In fact, the GMAO has taken on the challenge of carrying out experimental decadal predictions in support of the IPCC AR5 effort.

Schubert, Siegfried↗