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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 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Estimated Ambient Sonic Boom Metric Levels and X-59 Signal-to-Noise Ratios across the USA

NASA is building the X-59 Quiet Supersonic Technology aircraft to produce low noise sonic booms for a series of community noise surveys across the USA. Survey participants will rate their perception of the low-booms from supersonic X-59 flyovers. Several noise metrics are proposed to quantify the noise dose: A-, B-, D-, and E-weighted Sound Exposure Level, Stevens Perceived Level, and Indoor Sonic Boom Annoyance Predictor. Sparse measurements across the survey area will be used to estimate community noise exposure. The level of these low-booms may be comparable to the ambient noise level in some locations, leading to uncertainty in noise exposure estimations. This uncertainty may necessitate increased reliance on sonic boom propagation predictions for exposure estimation. Low-boom signal to ambient noise ratio is one way to quantify uncertainty in measured sonic boom levels. An empirical relationship between A-weighted ambient level and sonic boom metric levels is used in conjunction with the National Park Service’s L50 SPL map to estimate ambient noise levels expressed in terms of sonic boom noise metrics across the USA. These estimates of ambient levels will aid in X-59 community test planning and execution. The signal-to-noise ratio for the undertrack X-59 sonic boom is also estimated, and an example application of these data is presented for comparing potential noise monitor sites prior to a community noise test.

X-59↗
NASA NTRS2022

Probing Dark Current Random Telegraph Signal in a Small Pitch Vertically Pinned Photodiode CMOS Image Sensor after Proton Irradiation

Dark Current degradation and Dark Current Ran- dom Telegraph Signal after proton irradiation are studied in new scale silicon microvolumes by using a commercial CMOS Image Sensor. Results show that previously reported empirical models describing the Displacement Damage induced degradations are still valid despite the 10 to 100 times smaller depletion volume used. In addition, no evidence of significant Total Ionizing Dose effects is observed. Finally the reduction of the fraction of Random Telegraph Signal (RTS) pixels detected and of the fraction of multi-level RTS pixels is directly linked to the reduction in pixel volume.

CMOS Image Sensor (CIS)↗
NASA NTRS2024

Initial Results of Wyatt EIRP- The Ground Based Power and Ambiguity Function Monitor for P-Band Signals of Opportunity Sources

The Wideband Year-round AmbuguiTy-function Track-ing Effective Isotropic Radiated Power (WYATT EIRP)instrument is designed to support P-Band based Sig-nals of Opportunity (SoOp) remote sensing instrument.SoOp utilizes pre-existing non-cooperative microwavetransmitters as sources of illumination. This remotesensing method requires knowledge of the signals EIRP,position and ambugituty function’s shape.WYATT EIRP is designed to periodically generateEIRP measurements, ambuguity functions and transmit-ter elevation. It uses an array of RHCP and LHCPantennas, mounted on a rotating antenna pedestal togenerate EIRP measurements. A secondary observationantenna is placed to allow time difference of arrival mea-surements for transmitter elevation estimates. Both thepedestal and reference antenana are used to generateamituigyt fionctions. The pedestal will also be used tovalidate existing P-Band background noise temperaturesky maps. WYATT EIRP will be commissioned in thefirst quarter of 2024 and will be used to provide calibra-tion data to the upcoming spaceborne SigNals Of Op-portunity: P-Band Investigation (SNOOPI) instrument.

Remote Sensing↗
NASA NTRS2024

Improved Soil Moisture Estimation and Detection of Irrigation Signal By Incorporating SMAP Soil Moisture Into the Indian Land Data Assimilation System (ILDAS)

Land surface models have facilitated the estimation of soil moisture over a range of spatiotemporal scales. However, limitations in model parameterization and under-representation of anthropogenic processes restrict their ability to estimate local-scale soil moisture variability, especially over irrigated areas. Assimilation of satellite-based soil moisture retrievals into land surface models can be a viable approach to overcome these constraints, specially over highly irrigated countries such as India, where such applications are rare. Additionally, large-scale validation of modeled soil moisture has been limited over India till now due to lack of a representative station network. By assimilating Soil Moisture Active Passive (SMAP)-based estimates into the state-of-the-art Indian Land Data Assimilation System (ILDAS) and combining with a new soil moisture station network of more than 200 stations, this study demonstrates improved soil moisture estimations and capture of irrigation signals over the region. The Noah-MP land surface model is forced by multiple local and global meteorological datasets and Ensemble Kalman Filter (EnKF) is used for assimilation of soil moisture. Comparison of open-loop and data assimilated soil moisture against station soil moisture data shows relative spatial mean improvement of 0.0178 in correlation and 0.0029 m3/m3 in RMSE. Further statistical comparison with in-situ data has also shown better results over most of the stations, as evident from improved correlations and reduced unbiased RMSE after assimilation. Finally, the climatology of soil moisture over the different irrigation fractions reveals that data assimilated outputs over irrigated grid cells tend to have higher soil moisture during dry winter season, demonstrating the ability to capture irrigation signals. These findings quantify the value of data assimilation in improving soil moisture estimates and the ability to capture unmodeled processes such as irrigation, which lays the science groundwork for upcoming space missions such as NASA ISRO Synthetic Aperture Radar (NISAR).

Soil Moisture↗
NASA NTRS1960

Some Characteristics of the Signal Received from 1958 Delta 2

The study of the rapid fluctuation in the received signal strength from artificial earth satellites has led to a better understanding of the irregularities in electron density which exist in the ionosphere. In particular, the dimensions and locations of these inhomogeneities have been investigated. This note may serve as additional confirmation of some of the work mentioned above and, in addition, will report several new features of the received satellite radio signals.

De Mendonca, F.↗
NASA NTRS1967

Video synchronization processor overcomes poor signal-to-noise ratio

Video synchronization processor overcomes poor signal-to-noise ratio which occurs during adverse signal conditions caused by flame attenuation, antenna pattern nulls, and near-horizon tracking. The system maintains sync lock far below the point where excessive noise would normally render the video useless.

Webb, D. L.↗
NASA NTRS1969

Data processing method for a weak, moving telemetry signal

Method of processing data from a spacecraft, where the carrier has a low signal-to-noise ratio and wide unpredictable frequency shifts, consists of analogue recording of the noisy signal along with a high-frequency tone that is used as a clock to trigger a digitizer.

Kendall, W. B.↗
NASA NTRS1969

Pulse-code-modulation baseline correction for low signal-to-noise ratios

Time-shared integrate-hold-dump circuits separate the dc level due to the signal /bit information/ from the dc signal due to the baseline error. The system detects the baseline error, filters it, and then algebraically adds enough voltage to a servo loop to reduce the error to zero.

Stephens, T. J.↗