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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1977

Velocity autocorrelation functions of Lennard-Jones fluids

By a self-consistent procedure, the velocity autocorrelation functions of both liquid and gaseous argon have been calculated without introducing any arbitrary parameters. The results are in satisfactory agreement with computer experiments. The correlation functions are primarily determined by the nearest-neighbor coordination. Because of the strong hard-core repulsion, the behaviors are more vibratory and damp out quickly at high densities and are more diffusive at lower densities.

Tsang, T.↗
NASA NTRS1980

Preliminary evidence for the influence of physiography and scale upon the autocorrelation function of remotely sensed data

Previously established results demonstrate that LANDSAT data are autocorrelated and can be described by a univariate linear stochastic process known as auto-regressive-integrated-moving-average model of degree 1, 0, 1 or ARIMA (1, 0, 1). This model has two coefficients of interest for interpretation phi(1) and theta(1). In a comparison of LANDSAT thematic mapper simulator (TMS) data and LANDSAT MSS data several results were established: (1) The form of the relatedness as described by this model is not dependent upon system look angle or pixel size. (2) The phi(1) coefficient increases with decreasing pixel size and increasing topographic complexity. (3) Changes in topography have a greater influence upon phi(1) than changes in land cover class. (4) The theta(1) seems to vary with the amount of atmospheric haze. These patterns of variation in phi(1) and theta(1) are potentially exploitable by the remote sensing community to yield stochastically independent sets of observations, characterize topography, and reduce the number of bytes needed to store remotely sensed data.

Labovitz, M. L.↗
NASA NTRS1985

Periodic binary sequences with very good autocorrelation properties

Computer searches were performed using both an 8086 microprocessor and a Cyber 750 mainframe to find repeated binary phase coded waveforms with very good matched and mismatched autocorrelation properties. The best results for every period up to 64 are given. Sequences with optimal peak sidelobes were discovered for each of these periods. These sequences have extensive applications in radar and communications, particularly in situations when there are very unfavorable signal-to-noise ratios. The best sequence of period 64 when processed using a mismatched filter giving no sidelobes has a reduction in the main lobe of less than 0.23 dB.

Tyler, S.↗
NASA NTRS1988

Atmospheric profiling of water vapour with a 20.5-23.5 GHz autocorrelation radiometer

A tropospheric water vapor profiling system is presented. The hardware consists of an upward looking radiometer (CORRAD) deployed at ground level. The CORRAD measures the autocorrelation of the downwelling thermal emission from the atmosphere over a passband of 20.5 to 23.5 GHz out to a maximum time delay of 6.1 ns. This produces 100 MHz resolution imaging of the complete emission spectrum about the 22.235 GHz water vapor resonance line. The 31 equivalent frequency channels produced by Fourier transformation of the data provide additional constraints on the inversion process required to estimate the water vapor profile, as compared to standard 2 to 5 frequency channel profiling systems. The CORRAD hardware is described, and radiometer and radiosonde profiles are compared.

Ruff, C. S.↗
NASA NTRS1989

The autocorrelation properties of fluctuations in the cosmic X-ray background

The HEAO 1 A-2 all-sky survey data have been analyzed to investigate the autocorrelation function of the surface brightness fluctuations of the extragalactic 2-10 keV X-ray background on angular scales ranging from 3 to 27 deg. The derived upper limits are compatible with optical estimates of the spatial correlation function of Abell's clusters and set interesting constraints on possible AGN clustering.

Persic, M.↗
NASA NTRS1989

Studies in astronomical time series analysis. III - Fourier transforms, autocorrelation functions, and cross-correlation functions of unevenly spaced data

This paper develops techniques to evaluate the discrete Fourier transform (DFT), the autocorrelation function (ACF), and the cross-correlation function (CCF) of time series which are not evenly sampled. The series may consist of quantized point data (e.g., yes/no processes such as photon arrival). The DFT, which can be inverted to recover the original data and the sampling, is used to compute correlation functions by means of a procedure which is effectively, but not explicitly, an interpolation. The CCF can be computed for two time series not even sampled at the same set of times. Techniques for removing the distortion of the correlation functions caused by the sampling, determining the value of a constant component to the data, and treating unequally weighted data are also discussed. FORTRAN code for the Fourier transform algorithm and numerical examples of the techniques are given.

Scargle, Jeffrey D.↗
NASA NTRS1994

How cosmic microwave background correlations at large angles relate to mass autocorrelations in space

The Sachs-Wolfe effect is known to produce large angular scale fluctuations in the cosmic microwave background radiation (CMBR) due to gravitational potential fluctuations. We show how the angular correlation function of the CMBR can be expressed explicitly in terms of the mass autocorrelation function xi(r) in the universe. We derive analytic expressions for the angular correlation function and its multipole moments in terms of integrals over xi(r) or its second moment, J(sub 3)(r), which does not need to satisfy the sort of integral constraint that xi(r) must. We derive similar expressions for bulk flow velocity in terms of xi and J(sub 3). One interesting result that emerges directly from this analysis is that, for all angles theta, there is a substantial contribution to the correlation function from a wide range of distance r and that radial shape of this contribution does not vary greatly with angle.

Blumenthal, George R.↗
NASA NTRS2008

TDR Using Autocorrelation and Varying-Duration Pulses

In an alternative to a prior technique of time-domain-reflectometry (TDR) in which very short excitation pulses are used, the pulses have very short rise and fall times and the pulse duration is varied continuously between a minimum and a maximum value. In both the present and prior techniques, the basic idea is to (1) measure the times between the generation of excitation pulses and the reception of reflections of the pulses as indications of the locations of one or more defects along a cable and (2) measure the amplitudes of the reflections as indication of the magnitudes of the defects. In general, an excitation pulse has a duration T. Each leading and trailing edge of an excitation pulse generates a reflection from a defect, so that a unique pair of reflections is associated with each defect. In the present alternative technique, the processing of the measured reflection signal includes computation of the autocorrelation function R(tau) identical with fx(t)x(t-tau)dt where t is time, x(t) is the measured reflection signal at time t, and taus is the correlation interval. The integration is performed over a measurement time interval short enough to enable identification and location of a defect within the corresponding spatial interval along the cable. Typically, where there is a defect, R(tau) exhibits a negative peak having maximum magnitude for tau in the vicinity of T. This peak can be used as a means of identifying a leading-edge/trailing-edge reflection pair. For a given spatial interval, measurements are made and R(tau) computed, as described above, for pulse durations T ranging from the minimum to the maximum value. The advantage of doing this is that the effective signal-to-noise ratio may be significantly increased over that attainable by use of a fixed pulse duration T.

Lucena, Angel↗
NASA NTRS2019

Interference Mitigation Using Cyclic Autocorrelation and Multi-Objective Optimization

Radio frequency interference on space-to-ground communications links can degrade performance and disrupt the transfer of critical data. These interference events become increasingly likely as more users enter the spectrum, due in part to shared spectrum allocations and scheduling conflicts. If this interference could be detected and mitigated by an automated system, then link performance and reliability in these scenarios could be improved. This report describes the implementation and evaluation of an automated interference mitigation system that provides this functionality. The system uses Cyclic Autocorrelation (CAC) signal processing techniques to monitor the spectrum and detect interfering signals, and it applies a multi-objective optimization approach to mitigate interference by changing link parameters to continuously optimize the link. The implementation was evaluated to characterize its signal detection capabilities for various link qualities and to compare its link management performance to Adaptive Coding and Modulation (ACM) and Constant Coding and Modulation (CCM) when in the presence of randomized interference. In the latter evaluation, the interference mitigation system achieved the highest average throughput in each tested scenario. With these results, the proposed solution provides the groundwork for further automated link management capabilities and continued investigation into interference mitigation approaches.

Interference mitigation↗