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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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NASA NTRS1995

Noise correlations in cosmic microwave background experiments

Many analysis of microwave background experiments neglect the correlation of noise in different frequency of polarization channels. We show that these correlations, should they be present, can lead to serve misinterpretation of an experiment. In particular, correlated noise arising from either electronics or atmosphere may mimic a cosmic signal. We quantify how the likelihood function for a given experiment varies with noise correlation, using both simple analytic models and actual data. For a typical microwave background anisotropy experiment, noise correlations at the level of 1% of the overall noise can seriously reduce the significance of a given detection.

Dodelson, Scott↗
NASA NTRS1995

Performance of residual carrier array-feed combining in correlated noise

An array feed combining system for the recovery of signal-to-noise ratio (SNR) loss due to antenna reflector deformation has been implemented and is currently being evaluated on the Jet Propulsion Laboratory's 34-meter DSS-13 antenna. In this system, the defocused signal field captured by a focal plane array feed is recovered using real-time signal-processing and signal-combining techniques. The current signal-processing and signal-combining algorithms are optimum under the assumption that the white Gaussian noise processes in the received signals from different array elements are mutually uncorrelated. Experimental data at DSS 13 indicate that these noise processes are indeed mutually correlated. The main result of this article is an analytical derivation of the actual SNR performance of the current suboptimal signal-combining algorithm in this correlated-noise environment. The analysis here shows that the combined signal SNR can either be improved or degraded depending on the relation between the array signal and noise correlation coefficient phases. Further performance improvement will require the development of signal-combining methods that take into account the correlated noises.

Tan, H. H.↗
NASA NTRS1995

Performance of Residual Carrier Array Feed Combining in Correlated Noise

An array feed combining system for the recovery of SNR loss due to antenna reflector deformation has been implemented and is currently being evaluated on the Jet Propulsion Laboratory 34 meter DSS-13 antenna. In this system, the defocused signal field captured by a focal plane array feed is recovered using real-time signal processing and signal combining techniques. The current signal processing and signal combining algorithms are optimum under the assumption that the white Gaussian noise processes in the received signals from different array elements are mutually uncorrelated. Experimental data at DSS-13 indicate that these noise processes are indeed mutually correlated. The main result of this paper is an analytical derivation of the actual SNR performance of the current suboptimal signal combining algorithm in this correlated noises environment. The analysis here shows that the combined signal SNR can either be improved or degraded depending on the relation between the array signal and noise correlation coefficient phases. Further performance improvement will require the development of signal combining methods that take into account the correlated noises.

Residual↗
NASA NTRS1993

The Effects of Correlated Noise in Phased-Array Observations of Radio Sources

Arrays of radio telescopes are now routinely used to provide increased signal-to-noise when obseving faint point sources. However, calculation of the achievable sensitivity is complicated if there are sources in the field of view other than the target source. These additional sources not only increase the system temperatures of the individual antennas, but may also contribute significant

radio↗
NASA NTRS1992

The effects of correlated noise in intra-complex DSN arrays for S-band Galileo telemetry reception

A number of the proposals for supporting a Galileo S-band (2.3-GHz) mission involve arraying several antennas to maximize the signal-to-noise ratio (and bit rate) obtainable from a given set of antennas. Arraying is no longer a new idea, having been used successfully during the Voyager encounters with Uranus and Neptune. However, arraying for Galileo's tour of Jupiter is complicated by Jupiter's strong radio emission, which produces correlated noise effects. This article discusses the general problem of correlated noise due to a planet, or other radio source, and applies the results to the specific case of an array of antennas at the DSN's Tidbinbilla, Australia, complex (DSS 42, DSS 43, DSS 45, and the yet-to-be-built DSS 34). The effects of correlated noise are highly dependent on the specific geometry of the array and on the spacecraft-planet configuration; in some cases, correlated noise effects produce an enhancement, rather than a degradation, of the signal-to-noise ratio. For the case considered here--an array of the DSN's Australian antennas observing Galileo and Jupiter--there are three regimes of interest. If the spacecraft-planet separation is approximately less than 75 arcsec, the average effect of correlated noise is a loss of signal to noise (approximately 0.2 dB as the spacecraft-planet separation approaches zero). For spacecraft-planet separations approximately greater than 75 arcsec, but approximately less than 400 arcsec, the effects of correlated noise cause signal-to-noise variations as large as several tenths of a decibel over time scales of hours or changes in spacecraft-planet separation of tens of arcseconds; however, on average its effects are small (less than 0.01 dB). When the spacecraft is more than 400 arcsec from Jupiter (as is the case for about half of Galileo's tour), correlated noise is a less than 0.05-dB effect.

Dewey, R. J.↗
NASA NTRS1995

Effects of correlated noise on the full-spectrum combining and complex-symbol combining arraying techniques

The process of combining telemetry signals received at multiple antennas, commonly referred to as arraying, can be used to improve communication link performance in the Deep Space Network (DSN). By coherently adding telemetry from multiple receiving sites, arraying produces an enhancement in signal-to-noise ratio (SNR) over that achievable with any single antenna in the array. A number of different techniques for arraying have been proposed and their performances analyzed in past literature. These analyses have compared different arraying schemes under the assumption that the signals contain additive white Gaussian noise (AWGN) and that the noise observed at distinct antennas is independent. In situations where an unwanted background body is visible to multiple antennas in the array, however, the assumption of independent noises is no longer applicable. A planet with significant radiation emissions in the frequency band of interest can be one such source of correlated noise. For example, during much of Galileo's tour of Jupiter, the planet will contribute significantly to the total system noise at various ground stations. This article analyzes the effects of correlated noise on two arraying schemes currently being considered for DSN applications: full-spectrum combining (FSC) and complex-symbol combining (CSC). A framework is presented for characterizing the correlated noise based on physical parameters, and the impact of the noise correlation on the array performance is assessed for each scheme.

Vazirani, P.↗
NASA NTRS1994

Correlated noise in the COBE DMR sky maps

The Cosmic Background Explorer Satellite Differential Radiometer (COBE DMR) sky maps contain low-level correlated noise. We obtain estimates of the amplitude and pattern of the correlated noise from three techniques: angular averages of the covariance matrix, Monte Carlo simulations of two-point correlation functions and direct analysis of the DMR maps. The results from the three methods are mutually consistent. The noise covariance matrix of a DMR sky maps is diagonal to an accuracy of better than 1%. For a given sky pixel, the dominant noise covariance occure with the ring of pixels at an angular separation of 60 deg due to the 60 deg separation of the DMR horns. The mean covariance at 60 deg is 0.45%((sup +0.18)(sub -0.14)) of the mean variance. Additionally, the variance in a given pixel is 0.7% greater than would be expected from a single beam experiment with the same noise properties. Autocorrelation functions suffer from a approximately 1.5 sigma positive bias at 60 deg while cross-correlations have no bias. Published COBE DMR results are not significantly affected by correlated noise.

Lineweaver, C. H.↗
NASA NTRS1996

Optimum combining of residual carrier array signals in correlated noises

An array feed combining system for the recovery of signal-to-noise ratio (SNR) loss due to antenna reflector deformation has been implemented and is currently being evaluated on the Jet Propulsion Laboratory 34-m DSS-13 antenna. The current signal-combining system operates under the assumption that the white Gaussian noise processes in the received signals from different array elements are mutually uncorrelated. However, experimental data at DSS 13 indicate that these noise processes are indeed mutually correlated. The objective of this work is to develop a signal-combining system optimized to account for the mutual correlations between these noise processes. The set of optimum combining weight coefficients that maximizes the combined signal SNR in the correlated noises environment is determined. These optimum weights depend on unknown signal and noise covariance parameters. A maximum-likelihood approach is developed to estimate these unknown parameters to obtain estimates of the optimum weight coefficients based on residual carrier signal samples. The actual combined signal SNR using the estimated weight coefficients is derived and shown to converge to the maximum achievable SNR as the number of signal samples increases. These results are also verified by simulation. A numerical example shows a significant improvement in SNR performance can be obtained, especially when the amount of correlation increases.

Liang, R.↗
NASA NTRS1996

Optimum Combining of Residual Carrier Array Signals in Correlated Noises

An array feed combining system for the recovery of signal-to-noise ratio (SNR) loss due to antenna reflector deformation has been implemented and is currently being evaluated on the Jet Propulsion Laboratory 34-m DSS-13 antenna. The current signal-combining system operates under the assumption that the white Gaussian noise processes in the received signals from different array elements are mutually uncorrelated. However, experimental data at DSS 13 indicate that these noise processes are indeed mutually correlated. The objective of this work is to develop a signal-combining system optimized to account for the mutual correlations between these noise processes. The set of optimum combining weight coefficients that maximizes the combined signal SNR in the correlated noises environment is determined. These optimum weights depend on unknown signal and noise covariance parameters. A maximum-likelihood approach is developed to estimate these unknown parameters to obtain estimates of the optimum weight coefficients based on residual carrier signal samples. The actual combined signal SNR using the estimated weight coefficients is derived and shown to converge to the maximum achievable SNR as the number of signal samples increases. These results are also verified by simulation. A numerical example shows a significant improvement in SNR performance can be obtained, especially when the amount of correlation increases.

Tan, H. H.↗
NASA NTRS2011

Effects of Tropospheric Spatio-Temporal Correlated Noise on the Analysis of Space Geodetic Data

The standard VLBI analysis models measurement noise as purely thermal errors modeled according to uncorrelated Gaussian distributions. As the price of recording bits steadily decreases, thermal errors will soon no longer dominate. It is therefore expected that troposphere and instrumentation/clock errors will increasingly become more dominant. Given that both of these errors have correlated spectra, properly modeling the error distributions will become more relevant for optimal analysis. This paper will discuss the advantages of including the correlations between tropospheric delays using a Kolmogorov spectrum and the frozen ow model pioneered by Treuhaft and Lanyi. We will show examples of applying these correlated noise spectra to the weighting of VLBI data analysis.

thermal noise↗
NASA NTRS2012

Effects of Tropospheric Spatio-Temporal Correlated Noise on the Analysis of Space Geodetic Data

The standard VLBI analysis models the distribution of measurement noise as Gaussian. Because the price of recording bits is steadily decreasing, thermal errors will soon no longer dominate. As a result, it is expected that troposphere and instrumentation/clock errors will increasingly become more dominant. Given that both of these errors have correlated spectra, properly modeling the error distributions will become increasingly relevant for optimal analysis. We discuss the advantages of modeling the correlations between tropospheric delays using a Kolmogorov spectrum and the frozen flow assumption pioneered by Treuhaft and Lanyi. We then apply these correlated noise spectra to the weighting of VLBI data analysis for two case studies: X/Ka-band global astrometry and Earth orientation. In both cases we see improved results when the analyses are weighted with correlated noise models vs. the standard uncorrelated models. The X/Ka astrometric scatter improved by approx.10% and the systematic Delta delta vs. delta slope decreased by approx. 50%. The TEMPO Earth orientation results improved by 17% in baseline transverse and 27% in baseline vertical.

instrumentation errors↗
NASA NTRS1994

The effects of correlated noise in phased-array observations of radio sources

Arrays of radio telescopes are now routinely used to provide increased signal-to-noise when observing faint point sources. However, calculation of the achievable sensitivity is complicated if there are sources in the field of view other than the target source. These additional sources not only increase the system temperatures of the individual antennas, but may also contribute significant 'correlated noise' to the effective system temperature of the array. This problem has been of particular interest in the context of tracking spacecraft in the vicinity of radio-bright planets (e.g., Galileo at Jupiter), but it has broader astronomical relevance as well. This paper presents a general formulation of the problem, for the case of a point-like target source in the presence of an additional radio source of arbitrary brightness distribution. We re-derive the well known result that, in the absence of any background sources, a phased array of N indentical antennas is a factor of N more sensitive than a single antenna. We also show that an unphased array of N identical antennas is, on average, no more sensitive than a single antenna if the signals from the individual antennas are combined prior to detection. In the case where a background source is present we show that the effects of correlated noise are highly geometry dependent, and for some astronomical observations may cause significant fluctuations in the array's effective system temperature.

Dewey, Rachel J.↗