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At least 55 records · Page 3

Signal-to-noise ratios of multiplexing spectrometers in high backgrounds

Signal-to-noise ratios and the amount of multiplexing gain achieved with a Michelson spectrometer during detector and background noise are studied. Noise caused by the warm background is found in 10 and 20-micron atmospheric windows in high resolution Fourier spectroscopy. An equation is derived for the signal-to-noise ratio based on the number of channels, total time to obtain the complete spectrum, the signal power in one spectral element, and the detector noise equivalent power in the presence of negligible background. Similar expressions are derived for backgrounds yielding a noise equivalent power to a spectral element, and backgrounds having flat spectra in the frequency range under investigation.

Knacke, R. F.↗

Signal-Induced Noise Effects in a Photon Counting System for Stratospheric Ozone Measurement

Signal-induced noise (SIN) is a common effect resulting when a photomultiplier tube (PMT) is saturated, for a brief moment, with a high intensity light pulse. After the laser pulse is sent into the atmosphere a very large light return, from either the near-field or a cloud, causes the PMT to momentarily saturate. The PMT is gated off at this time so no signal is seen at the anode. When the PMT gate is turned on, the far-field light return from the atmosphere is observed. This signal is distorted, however because of the addition of SIN to the received light signal causing a slower than expected decay of the atmospheric signal return. We have characterized SIN responses to varying parameters of the incident light on the PMT. These varied parameters included incident wavelength, PMT voltage, incident intensity, and tube type. We found that only the amplitude of the SIN was effected by varying PMT voltages and light intensities. The amplitude increased linearly as input light intensity increased. Different incident wavelengths at the same intensity did not effect the amplitude or the temporal behavior of the SIN response. Finally, different PMT tubes with similar physical structures exhibited similar SIN responses although with different amplitudes. The different amplitudes can be attributed to the different gains and operating voltages of each tube. These results suggest that SIN is caused by photocathode electron dynamics such as charge accumulation on internal PMT surfaces. These surfaces then emit the electrons slowly resulting in a long decay noise signal. With the SIN responses characterized we can now try to develop a method to reduce or eliminate SIN in DIAL systems.

Harper, David B.↗

A New Method for Reduction of Photomultiplier Signal-Induced Noise

For lidar measurements of ozone, photomultiplier tube (PMT) detector signal-induced noise represents a fundamental problem that complicates the extraction of information from lidar data. A new method is developed to significantly reduce signal-induced noise in lidar receiver PMT detectors. The electron optics of the lidar photomultiplier detector is modified to filter the source of signal-induced noise. A mesh electrode external to the PMT is utilized to control photoemission and disorient electron trajectories from the photocathode to the first dynode. Experiments were taken both with simulated and actual lidar return signals at Langley Research Center. Results show at least 40 percent more accurate ozone number density values with a mesh voltage of 60 V applied than with no voltage applied.

Koble, Andrea↗

Signal-to-noise ratios in coherent soft limiters

Expressions for the output signal-to-noise power ratio of a bandpass soft limiter followed by a coherent detection device are presented and discussed. It is found that a significant improvement in the output signal-to-noise ratio at low input SNRs can be achieved by such soft limiters as compared to hard limiters. This indicates that the soft limiter may be of some use in the area of threshold extension. Approximation methods for determining output signal-to-noise spectral densities are also presented.

Lesh, J. R.↗

Signal-to-noise ratios in coherent soft limiters

Expressions for the output signal-to-noise power ratio of a bandpass soft limiter followed by a coherent detection device are presented and discussed. It is found that a significant improvement in the output signal-to-noise ratio (SNR) at low input SNR's can be achieved by such soft limiters as compared to hard limiters. This indicates that the soft limiter may be of some use in the area of threshold extension. Approximation methods for determining output signal-to-noise spectral densities are also presented.

Lesh, J. R.↗

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.↗

Real-time Signal-to-noise Ratio (SNR) Estimation for BPSK and QPSK Modulation Using the Active Communications Channel

Method and apparatus for estimating signal-to-noise ratio (SNR) gamma of a composite input signal e(t) on a phase modulated (e.g., BPSK) communications link. A first demodulator receives the composite input signal and a stable carrier signal and outputs an in-phase output signal; a second demodulator receives the composite input signal and a phase-shifted version of the carrier signal and outputs a quadrature-phase output signal; and phase error theta(sub E)(t) contained within the composite input signal e(t) is calculated from the outputs of the first and second demodulators. A time series of statistically independent phase error measurements theta(sub E)(t(sub 1)), theta (sub E)(t(sub 2)),..., theta (sub E)(t(sub k)) is obtained from the composite input signal subtending a time interval delta t = t(sub k) - t(sub 1) whose value is small enough such that gamma(t) and sigma(t) can be taken to be constant in delta t. A biased estimate gamma(sup *) for the signal-to-noise ratio (SNR) gamma if the composite input signal is calculated using maximum likelihood (ML) estimation techniques, and an unbiased estimate gamma(sup ^) for the signal-to-noise ratio (SNR) gamma of the composite input signal is determined from the biased estimate gamma(sup *), such as by use of a look-up table.

Manning, Robert M.↗

Optimal Correlation Filters for Images with Signal-Dependent Noise

We address the design of optimal correlation filters for pattern detection and recognition in the presence of signal-dependent image noise sources. The particular examples considered are film-grain noise and speckle. Two basic approaches are investigated: (1) deriving the optimal matched filters for the signal-dependent noise models and comparing their performances with those derived for traditional signal-independent noise models and (2) first nonlinearly transforming the signal-dependent noise to signal-independent noise followed by the use of a classical filter matched to the transformed signal. We present both theoretical and computer simulation results that demonstrate the generally superior performance of the second approach in terms of the correlation peak signal-to-noise ratio.

Downie, John D.↗

Signal-to-noise ratio for the wide field-planetary camera of the Space Telescope

Signal-to-noise ratios for the Wide Field Camera and Planetary Camera of the Space Telescope were calculated as a function of integration time. Models of the optical systems and CCD detector arrays were used with a 27th visual magnitude point source and a 25th visual magnitude per arc-sq. second extended source. A 23rd visual magnitude per arc-sq. second background was assumed. The models predicted signal-to-noise ratios of 10 within 4 hours for the point source centered on a signal pixel. Signal-to-noise ratios approaching 10 are estimated for approximately 0.25 x 0.25 arc-second areas within the extended source after 10 hours integration.

Zissa, D. E.↗

Signal-to-noise considerations for sky-subtracted CCD data

The standard equation for calculating the uncertainty of photometry obtained from CCDs does not correctly consider the random errors, or 'noise', introduced into observations by procedures used in reducing the data. This paper presents a thorough derivation of the theoretical error equation that considers the contributions from all internal noise sources in the signal-to-noise ratio (S/N) of a sky-subtracted image. A simplified version used for estimating the internal errors from empirical data is also derived. The propagation of noise through the data-reduction process is illustrated through a series of equations for the change in S/N that results from a variety of different operations performed on a CCD frame. Comparing these effects with the results expected for an observation made with an ideal detector suggests a number of ways to improve the precision of photometry through the practices employed in obtaining and reducing the observations.

Newberry, Michael V.↗

Algorithm for astronomical, point source, signal to noise ratio calculations

An algorithm was developed to simulate the expected signal to noise ratios as a function of observation time in the charge coupled device detector plane of an optical telescope located outside the Earth's atmosphere for a signal star, and an optional secondary star, embedded in a uniform cosmic background. By choosing the appropriate input values, the expected point source signal to noise ratio can be computed for the Hubble Space Telescope using the Wide Field/Planetary Camera science instrument.

Jayroe, R. R.↗

Signal to noise ratio calculation for fiber optics links

The signal to noise ratio (SNR) effect upon the maximum transmission length of a fiberoptic system is discussed. The relationships of different system parameters are discussed. A general formula to obtain the SNR of a single mode fiberoptic system is derived. The SNR attainable with single mode and multimode fiber optics links was calculated from fundamental noise considerations. It was found that for single mode fibers, laser noise dominates the noise contributions for links less than 30 km long, while thermal noise dominates for longer links. Multimode fibers degrade SNR for long links because of intermode dispersion. For frequency standard transmission, as long as the baseband modulation signals are within the bandwidth of the fibers, respectable SNR can be attained with low loss fibers (approximately 1 dB/km) for links as long as 70 km. For wideband transmission SNR is decreased by a factor equal to the ratio of the bandwidth.

Lau, K. Y.↗

Estimating the signal-to-noise ratio of AVIRIS data

To make the best use of narrowband airborne visible/infrared imaging spectrometer (AVIRIS) data, an investigator needs to know the ratio of signal to random variability or noise (signal-to-noise ratio or SNR). The signal is land cover dependent and varies with both wavelength and atmospheric absorption; random noise comprises sensor noise and intrapixel variability (i.e., variability within a pixel). The three existing methods for estimating the SNR are inadequate, since typical laboratory methods inflate while dark current and image methods deflate the SNR. A new procedure is proposed called the geostatistical method. It is based on the removal of periodic noise by notch filtering in the frequency domain and the isolation of sensor noise and intrapixel variability using the semi-variogram. This procedure was applied easily and successfully to five sets of AVIRIS data from the 1987 flying season and could be applied to remotely sensed data from broadband sensors.

Curran, Paul J.↗

An Algorithm for Statistical Audibility Prediction (SAP) of an Arbitrary Signal in the Presence of Noise

A method for predicting the audibility of an arbitrary time-varying noise (signal) in the presence of masking noise has been developed. The statistical audibility prediction (SAP) method relies on the specific loudness, or loudness perceived through the individual auditory filters, for accurate statistical estimation of audibility vs. time. More recent development has focused on derivation and inclusion of frequency-dependent correction factors in SAP’s model to account for the ability to hear signals below the level of the masking noise. Audibility prediction vs. time is intuitive since it captures changes in audibility with time as it occurs, which is critical for the study of human response to noise. Concurrently time-frequency prediction of audibility may also provide valuable information about the root cause(s) for audibility useful for the design and operation of sources of noise. Empirical data, gathered under a three-alternative forced-choice (3AFC) test paradigm for low-frequency sound, has been used to examine the accuracy of SAP.

audibility↗

Filter distortion effects on telemetry signal-to-noise ratio

The effect of filtering on the Signal-to-Noise Ratio (SNR) of a coherently demodulated band-limited signal is determined in the presence of worse-case amplitude ripple. The problem is formulated mathematically as an optimization problem in the L2-Hilbert space. The form of the worst-cast amplitude ripple is specified, and the degradation in the SNR is derived in a closed form expression. It is shown that when the maximum passband amplitude ripple is 2 delta (peak to peak), the SNR is degraded by at most (1 - delta squared), even when the ripple is unknown or uncompensated. For example, an SNR loss of less than 0.01 dB due to amplitude ripple can be assured by keeping the amplitude ripple to under 0.42 dB.

Sadr, R.↗