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At least 235 records · Page 13

A new method for the detection of a periodic signal of unknown shape and period

A method was developed for the detection and measurement of a periodic signal with unknown characteristics in a data set where the existence of such signal was not known. The method detects a signal by using Bayesian probability theory to compare a constant model for the signal to members of a class of models with periodic structure. The method was applied to simulated data generated with both stepwise and sinusoidal light curves, demonstrating that such signals can be sensitively detected and the signal frequency and its shape can be accurately estimated.

Gregory, P. C.↗

Coherent Doppler lidar signal covariance including wind shear and wind turbulence

The performance of coherent Doppler lidar is determined by the statistics of the coherent Doppler signal. The derivation and calculation of the covariance of the Doppler lidar signal is presented for random atmospheric wind fields with wind shear. The random component is described by a Kolmogorov turbulence spectrum. The signal parameters are clarified for a general coherent Doppler lidar system. There are two distinct physical regimes: one where the transmitted pulse determines the signal statistics and the other where the wind field dominates the signal statistics. The Doppler shift of the signal is identified in terms of the wind field and system parameters.

Frehlich, R. G.↗

Signal detection amid noise with known statistics

Conventional methods of signal detection are based on the comparison of a local signal-to-noise ratio S/N to some threshold value. We present a new method that compares instead the histogram of the data with the one expected for background noise alone. Signals are detected from discrepancies between the two. We expect it to be applicable in the detection of signals from any data whose background statistics is known. To illustrate the method, we apply it to the case of photon-limited imaging data where the underlying background is Poissonian. Numerical simulations are used to check the efficiency of our method, finding that for signals with low S/N (less than 5), it detects signals with a higher degree of reliability than the conventional method.

Zepka, A. F.↗

Magnetospheric and ionospheric signals in magnetic observatory monthly means: Electrical conductivity of the deep mantle

First differences of magnetic observatory monthly means for 1963-1982 were analyzed using techniques of spherical harmonics analysis and power spectral analysis. The external source signal is shown to be primarily zonal in geomagnetic coordinates. Prominent peaks are present in the power spectrum at frequencies of 1.0 cycle/yr and 2.0 cycles/yr. The annual signal is largest on the degree 2 external zonal spherical harmonic, while the semiannual signal is largest on the degree 1 and degree 3 external zonal spherical harmonics. The presence of the semiannual signal on odd-degree spherical harmonics and of the annual signal on even-degree spherical harmonics was predicted from symmetry considerations and the annual cycle of solar inclination. These signals are all modulated by the sunspot frequency and its harmonics. The degree 1 term is believed to be due mainly to magnetopause and ring currents while the degree 2 and degree 3 terms are believed to be due mainly to ionospheric currents. The degree 1 external zonal harmonic has a continuous spectrum in addition to the semiannual spectral peak. A corresponding degree 1 internal term is due to electromagnetic induction. The degree 1 continuous spectrum is useful for study of the electrical conductivity of the deep mantle. A global geomagnetic response function consistent with a mantle conductivity of about 10 S/m at the core-mantle boundary has been derived.

Mcleod, Malcolm G.↗

The influence of source acceleration on acoustic signals

The effect of aircraft acceleration on acoustic signals is often ignored in both analytical studies and data reduction of flight test measurements. In this study, the influence of source acceleration on acoustic signals is analyzed using computer simulated signals for an accelerating point source. Both rotating and translating sources are considered. Using a known signal allows an assessment of the influence of source acceleration on the received signal. Aircraft acceleration must also be considered in the measurement and reduction of flyover noise. Tracking of the aircraft over an array of microphones enables ensemble averaging of the acoustic signal, thus increasing the confidence in the measured data. This is only valid when both the altitude and velocity remain constant. For an accelerating aircraft, each microphone is exposed to differing flight velocities, Doppler shifts, and smear angles. Thus, averaging across the array in the normal manner is constrained by aircraft acceleration and microphone spacing. In this study computer simulated spectra, containing acceleration, are averaged across a 12 microphone array mimicking a flight test with accelerated profile in which noise data was obtained. Overlapped processing is performed is performed in the flight test measurements in order to alleviate spectral smearing.

Kelly, Jeffrey J.↗

Optical Correlation of Images With Signal-Dependent Noise Using Constrained-Modulation Filter Devices

Images with signal-dependent noise present challenges beyond those of images with additive white or colored signal-independent noise in terms of designing the optimal 4-f correlation filter that maximizes correlation-peak signal-to-noise ratio, or combinations of correlation-peak metrics. Determining the proper design becomes more difficult when the filter is to be implemented on a constrained-modulation spatial light modulator device. The design issues involved for updatable optical filters for images with signal-dependent film-grain noise and speckle noise are examined. It is shown that although design of the optimal linear filter in the Fourier domain is impossible for images with signal-dependent noise, proper nonlinear preprocessing of the images allows the application of previously developed design rules for optimal filters to be implemented on constrained-modulation devices. Thus the nonlinear preprocessing becomes necessary for correlation in optical systems with current spatial light modulator technology. These results are illustrated with computer simulations of images with signal-dependent noise correlated with binary-phase-only filters and ternary-phase-amplitude filters.

Downie, John D.↗

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

A significant source of error in making atmospheric differential absorption lidar ozone measurements is the saturation of the photomultiplier tube by the strong, near field light return. Some time after the near field light signal is gone, the photomultiplier tube gate is opened and a noise signal, called signal-induced noise, is observed. Research reported here gives experimental results from measurement of photomultiplier signal-induced noise. Results show that signal-induced noise has several decaying exponential signals, suggesting that electrons are slowly emitted from different surfaces internal to the photomultiplier tube.

Harper, David B.↗

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.↗

B and F Signal Conditioner Checkout Unit

ATK Thiokol Propulsion, Test Services uses B&F Signal Conditioning units to provide excitation power and shunt calibration information to the data recording systems. Gage measurements such as force, temperature, pressure, strain, etc. are recorded using this equipment. Approximately 2500 reusable instrumentation B&F Signal Conditioning units were purchased over an interval from 1978 to 1988 at a cost of around $1000 each. Through use and over time, the relay contacts on the signal conditioning mode cards have become corroded, resulting in excessive contact resistance. This causes inaccurate and inconsistent calibration data and could jeopardize the test results. These signal conditioning cards are needed for product testing for an estimated five more years, therefore, it is necessary to develop a solution to isolate the malfunctioning units for repair. The current screening method requires Test Area technicians to check cards manually, however the connections and measurements required for this process are inefficient and time consuming. To resolve this problem, funding was approved to design and build two B&F Signal Conditioner Checkout Units. Each unit will allow technicians to test relay contact resistance on signal conditioning mode cards before they are installed for data collection procedures. This tool will allow Test Area to resolve calibration accuracy problems and extend the life of the data acquisition equipment, as well as save troubleshooting time for the technicians.

Magleby, Alyssa↗

Acoustic Emission Signals in Thin Plates Produced by Impact Damage

Acoustic emission (AE) signals created by impact sources in thin aluminum and graphite/epoxy composite plates were analyzed. Two different impact velocity regimes were studied. Low-velocity (less than 0.21 km/s) impacts were created with an airgun firing spherical steel projectiles (4.5 mm diameter). High-velocity (1.8 to 7 km/s) impacts were generated with a two-stage light-gas gun firing small cylindrical nylon projectiles (1.5 mm diameter). Both the impact velocity and impact angle were varied. The impacts did not penetrate the aluminum plates at either low or high velocities. For high-velocity impacts in composites, there were both impacts that fully penetrated the plate as well as impacts that did not. All impacts generated very large amplitude AE signals (1-5 V at the sensor), which propagated as plate (extensional and/or flexural) modes. In the low-velocity impact studies, the signal was dominated by a large flexural mode with only a small extensional mode component detected. As the impact velocity was increased within the low velocity regime, the overall amplitudes of both the extensional and flexural modes increased. In addition, a relative increase in the amplitude of high-frequency components of the flexural mode was also observed. Signals caused by high-velocity impacts that did not penetrate the plate contained both a large extensional and flexural mode component of comparable amplitudes. The signals also contained components of much higher frequency and were easily differentiated from those caused by low-velocity impacts. An interesting phenomenon was observed in that the large flexural mode component, seen in every other case, was absent from the signal when the impact particle fully penetrated through the composite plates.

Prosser, William H.↗

Visual signal detection in structured backgrounds. II. Effects of contrast gain control, background variations, and white noise

Studies of visual detection of a signal superimposed on one of two identical backgrounds show performance degradation when the background has high contrast and is similar in spatial frequency and/or orientation to the signal. To account for this finding, models include a contrast gain control mechanism that pools activity across spatial frequency, orientation and space to inhibit (divisively) the response of the receptor sensitive to the signal. In tasks in which the observer has to detect a known signal added to one of M different backgrounds grounds due to added visual noise, the main sources of degradation are the stochastic noise in the image and the suboptimal visual processing. We investigate how these two sources of degradation (contrast gain control and variations in the background) interact in a task in which the signal is embedded in one of M locations in a complex spatially varying background (structured background). We use backgrounds extracted from patient digital medical images. To isolate effects of the fixed deterministic background (the contrast gain control) from the effects of the background variations, we conduct detection experiments with three different background conditions: (1) uniform background, (2) a repeated sample of structured background, and (3) different samples of structured background. Results show that human visual detection degrades from the uniform background condition to the repeated background condition and degrades even further in the different backgrounds condition. These results suggest that both the contrast gain control mechanism and the background random variations degrade human performance in detection of a signal in a complex, spatially varying background. A filter model and added white noise are used to generate estimates of sampling efficiencies, an equivalent internal noise, an equivalent contrast-gain-control-induced noise, and an equivalent noise due to the variations in the structured background.

NASA Discipline Space Human Factors↗

Empirical mode decomposition apparatus, method and article of manufacture for analyzing biological signals and performing curve fitting

A computer implemented physical signal analysis method includes four basic steps and the associated presentation techniques of the results. The first step is a computer implemented Empirical Mode Decomposition that extracts a collection of Intrinsic Mode Functions (IMF) from nonlinear, nonstationary physical signals. The decomposition is based on the direct extraction of the energy associated with various intrinsic time scales in the physical signal. Expressed in the IMF's, they have well-behaved Hilbert Transforms from which instantaneous frequencies can be calculated. The second step is the Hilbert Transform which produces a Hilbert Spectrum. Thus, the invention can localize any event on the time as well as the frequency axis. The decomposition can also be viewed as an expansion of the data in terms of the IMF's. Then, these IMF's, based on and derived from the data, can serve as the basis of that expansion. The local energy and the instantaneous frequency derived from the IMF's through the Hilbert transform give a full energy-frequency-time distribution of the data which is designated as the Hilbert Spectrum. The third step filters the physical signal by combining a subset of the IMFs. In the fourth step, a curve may be fitted to the filtered signal which may not have been possible with the original, unfiltered signal.

Huang, Norden E.↗

Empirical mode decomposition apparatus, method and article of manufacture for analyzing biological signals and performing curve fitting

A computer implemented physical signal analysis method includes four basic steps and the associated presentation techniques of the results. The first step is a computer implemented Empirical Mode Decomposition that extracts a collection of Intrinsic Mode Functions (IMF) from nonlinear, nonstationary physical signals. The decomposition is based on the direct extraction of the energy associated with various intrinsic time scales in the physical signal. Expressed in the IMF's, they have well-behaved Hilbert Transforms from which instantaneous frequencies can be calculated. The second step is the Hilbert Transform which produces a Hilbert Spectrum. Thus, the invention can localize any event on the time as well as the frequency axis. The decomposition can also be viewed as an expansion of the data in terms of the IMF's. Then, these IMF's, based on and derived from the data, can serve as the basis of that expansion. The local energy and the instantaneous frequency derived from the IMF's through the Hilbert transform give a full energy-frequency-time distribution of the data which is designated as the Hilbert Spectrum. The third step filters the physical signal by combining a subset of the IMFs. In the fourth step, a curve may be fitted to the filtered signal which may not have been possible with the original, unfiltered signal.

Huang, Norden E.↗

Parallel Processing of Broad-Band PPM Signals

A parallel-processing algorithm and a hardware architecture to implement the algorithm have been devised for timeslot synchronization in the reception of pulse-position-modulated (PPM) optical or radio signals. As in the cases of some prior algorithms and architectures for parallel, discrete-time, digital processing of signals other than PPM, an incoming broadband signal is divided into multiple parallel narrower-band signals by means of sub-sampling and filtering. The number of parallel streams is chosen so that the frequency content of the narrower-band signals is low enough to enable processing by relatively-low speed complementary metal oxide semiconductor (CMOS) electronic circuitry. The algorithm and architecture are intended to satisfy requirements for time-varying time-slot synchronization and post-detection filtering, with correction of timing errors independent of estimation of timing errors. They are also intended to afford flexibility for dynamic reconfiguration and upgrading. The architecture is implemented in a reconfigurable CMOS processor in the form of a field-programmable gate array. The algorithm and its hardware implementation incorporate three separate time-varying filter banks for three distinct functions: correction of sub-sample timing errors, post-detection filtering, and post-detection estimation of timing errors. The design of the filter bank for correction of timing errors, the method of estimating timing errors, and the design of a feedback-loop filter are governed by a host of parameters, the most critical one, with regard to processing very broadband signals with CMOS hardware, being the number of parallel streams (equivalently, the rate-reduction parameter).

Gray, Andrew↗

Medical Signal-Conditioning and Data-Interface System

A general-purpose portable, wearable electronic signal-conditioning and data-interface system is being developed for medical applications. The system can acquire multiple physiological signals (e.g., electrocardiographic, electroencephalographic, and electromyographic signals) from sensors on the wearer s body, digitize those signals that are received in analog form, preprocess the resulting data, and transmit the data to one or more remote location(s) via a radiocommunication link and/or the Internet. The system includes a computer running data-object-oriented software that can be programmed to configure the system to accept almost any analog or digital input signals from medical devices. The computing hardware and software implement a general-purpose data-routing-and-encapsulation architecture that supports tagging of input data and routing the data in a standardized way through the Internet and other modern packet-switching networks to one or more computer(s) for review by physicians. The architecture supports multiple-site buffering of data for redundancy and reliability, and supports both real-time and slower-than-real-time collection, routing, and viewing of signal data. Routing and viewing stations support insertion of automated analysis routines to aid in encoding, analysis, viewing, and diagnosis.

Braun, Jeffrey↗

Estimating Effects of Multipath Propagation on GPS Signals

Multipath Simulator Taking into Account Reflection and Diffraction (MUSTARD) is a computer program that simulates effects of multipath propagation on received Global Positioning System (GPS) signals. MUSTARD is a very efficient means of estimating multipath-induced position and phase errors as functions of time, given the positions and orientations of GPS satellites, the GPS receiver, and any structures near the receiver as functions of time. MUSTARD traces each signal from a GPS satellite to the receiver, accounting for all possible paths the signal can take, including all paths that include reflection and/or diffraction from surfaces of structures near the receiver and on the satellite. Reflection and diffraction are modeled by use of the geometrical theory of diffraction. The multipath signals are added to the direct signal after accounting for the gain of the receiving antenna. Then, in a simulation of a delay-lock tracking loop in the receiver, the multipath-induced range and phase errors as measured by the receiver are estimated. All of these computations are performed for both right circular polarization and left circular polarization of both the L1 (1.57542-GHz) and L2 (1.2276-GHz) GPS signals.

Byun, Sung↗

Signal Design for Improved Ranging Among Multiple Transceivers

"Ultra-BOC" (where "BOC" signifies "binary offset carrier") is the name of an improved generic design of microwave signals to be used by a group of spacecraft flying in formation to measure ranges and bearings among themselves and to exchange telemetry needed for these measurements. Ultra-BOC could also be applied on Earth for diverse purposes -- for example, measuring relative positions of vehicles on highways for traffic-control purposes and determining the relative alignments of machines operating in mines and of construction machines and structures at construction sites. Ultra-BOC provides for rapid and robust acquisition of signals, even when signal-to-noise ratios are low. The design further provides that each spacecraft or other platform constantly strives to acquire and track the signals from the other platforms while simultaneously transmitting signals that provide full range, bearing, and telemetry service to the other platforms. In Ultra-BOC, unlike in other signal designs that have been considered for the same purposes, it is not necessary to maneuver the spacecraft or other platforms to obtain the data needed for resolving integer-carrier-cycle phase ambiguities.

Young, Lawrence↗

Low-Cutoff, High-Pass Digital Filtering of Neural Signals

The figure depicts the major functional blocks of a system, now undergoing development, for conditioning neural signals acquired by electrodes implanted in a brain. The overall functions to be performed by this system can be summarized as preamplification, multiplexing, digitization, and high-pass filtering. Other systems under development for recording neural signals typically contain resistor-capacitor analog low-pass filters characterized by cutoff frequencies in the vicinity of 100 Hz. In the application for which this system is being developed, there is a requirement for a cutoff frequency of 5 Hz. Because the resistors needed to obtain such a low cutoff frequency would be impractically large, it was decided to perform low-pass filtering by use of digital rather than analog circuitry. In addition, it was decided to timemultiplex the digitized signals from the multiple input channels into a single stream of data in a single output channel. The signal in each input channel is first processed by a preamplifier having a voltage gain of approximately 50. Embedded in each preamplifier is a low-pass anti-aliasing filter having a cutoff frequency of approximately 10 kHz. The anti-aliasing filters make it possible to couple the outputs of the preamplifiers to the input ports of a multiplexer. The output of the multiplexer is a single stream of time-multiplexed samples of analog signals. This stream is processed by a main differential amplifier, the output of which is sent to an analog-to-digital converter (ADC). The output of the ADC is sent to a digital signal processor (DSP).

Mojarradi,Mohammad↗