Signal to Noise Ratio Estimation of the ASCENDS CarbonHawk Experiment Simulator (ACES) for Atmospheric CO2 Measurement
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The daily global-mean values of the lower-tropospheric temperature determined from microwave emissions measured by satellites are examined in terms of their signal, noise, and signal-to-noise ratio. Daily and 30-day average noise estimates are reduced by, almost 50% and 35%, respectively, by analyzing and adjusting (if necessary) for errors due to (1) missing data, (2) residual harmonics of the annual cycle unique to particular satellites, (3) lack of filtering, and (4) spurious trends. After adjustments, the decadal trend of the lower-tropospheric global temperature from January 1979 through February 1994 becomes -0.058 C, or about 0.03 C per decade cooler than previously calculated.
The daily global-mean values of the lower-tropospheric temperature determined from microwave emissions measured by satellites are examined in terms of their signal, noise, and signal-to-noise ratio. Daily and 30-day average noise estimates are reduced by almost 50% and 35%. respectively, by analyzing and adjusting (if necessary) for errors due to 1) missing data, 2) residual harmonics of the annual cycle unique to particular satellites, 3) lack of filtering, and 4) spurious trends. After adjustments, the decadal trend of the lower-tropospheric global temperature from January 1979 through February 1994 becomes -0.058 C. or about 0.03 C per decade cooler than previously calculated.
Noise spectrum properties of low noise microwave tube and solid state signal sources
Signal design for Gaussian noise and intersymbol interference immunity, discussing bandlimited signals and maximum likelihood detection technique
Optimum linear filtering of integrated signal in white noise, deriving expression for minimum mean square error
The production of transient magnetic fields by hypervelocity meteoroid impact has been proposed to possibly explain the presence of paleomagnetic fields in certain lunar samples as well as across broader areas of the lunar surface. In an effort to understand the lunar magnetic record, continued experiments at the NASA Ames Vertical Gun Range allow characterizing magnetic fields produced by the 5 km/s impacts of 0.32-0.64 cm projectiles over a broad range of impact angles and projectile/target compositions. From such studies, another phenomenon has emerged, macroscopic electric charge separation, that may have importance for the magnetic state of solid-body surfaces. This phenomenon was observed during explosive cratering experiments, but the magnetic consequences of macroscopic electric charge separation (as opposed to plasma production) during explosion and impact cratering have not, to our knowledge, been explored before now. It is straightforward to show that magnetic field production due to this process may scale as a weakly increasing function of impactor kinetic energy, although more work is needed to precisely assess the scaling dependence. The original intent of our experiments was to assess the character of purely electrostatic signals for comparison with inferred electrostatic noise signals acquired by shielded magnetic sensors buried within particulate dolomite targets. The results demonstrated that electrostatic noise does affect the magnetic sensors but only at relatively short distances (less than 4 cm) from the impact point (our magnetic studies are generally performed at distances greater than approximately 5.5 cm). However, to assess models for magnetic field generation during impact, measurements are needed of the magnetic field as close to the impact point as possible; hence, work with an improved magnetic sensor design is in progress. In this paper, we focus on electric charge separation during hypervelocity impacts as a potential transient magnetic field production mechanism in its own right.
Report presents theoretical study of behavior of Costas loop in reception of radio carrier signal modulated in phase by sinusoidal or square-wave subcarrier, further modulated in phase by nonreturn-to-zero binary data signal. Phase and frequency of received signal affected by Doppler shift, and instantaneous amplitude of received signal corrupted by additive white Gaussian noise. Signals of this type ordinarily used in spacecraft telemetry, sine-wave subcarrier being preferred for shorter signal paths and square-wave subcarrier for longer signal paths.
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.
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.
An image sensor operable to vary the output spatial resolution according to a received light level while maintaining a desired signal-to-noise ratio. Signals from neighboring pixels in a pixel patch with an adjustable size are added to increase both the image brightness and signal-to-noise ratio. One embodiment comprises a sensor array for receiving input signals, a frame memory array for temporarily storing a full frame, and an array of self-calibration column integrators for uniform column-parallel signal summation. The column integrators are capable of substantially canceling fixed pattern noise.
Digital filters for detecting random signals in random noise