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We examine the question of whether or not the non-periodic Variations in solar activity are caused by a white-noise random process. The Hurst exponent, which characterizes the persistence of a time series, is evaluated for the series 14C Data for the time interval from about 6000BC to 1950 AD.
Aircraft system noise predictions have been performed for NASA modeled hybrid wing body aircraft advanced concepts with 2025 entry-into-service technology assumptions. The system noise predictions developed over a period from 2009 to 2016 as a result of improved modeling of the aircraft concepts, design changes, technology development, flight path modeling, and the use of extensive integrated system level experimental data. In addition, the system noise prediction models and process have been improved in many ways. An additional process is developed here for quantifying the uncertainty with a 95% confidence level. This uncertainty applies only to the aircraft system noise prediction process. For three points in time during this period, the vehicle designs, technologies, and noise prediction process are documented. For each of the three predictions, and with the information available at each of those points in time, the uncertainty is quantified using the direct Monte Carlo method with 10,000 simulations. For the prediction of cumulative noise of an advanced aircraft at the conceptual level of design, the total uncertainty band has been reduced from 12.2 to 9.6 EPNL dB. A value of 3.6 EPNL dB is proposed as the lower limit of uncertainty possible for the cumulative system noise prediction of an advanced aircraft concept.
Standard image processing techniques are not applicable to radar images because of the coherent nature of the sensor. Therefore there is a need to develop preprocessing techniques for radar images which will then allow these standard methods to be applied. A random field model for radar image data is developed. This model describes the image data as the result of a multiplicative-convolved process. Standard techniques, those based on additive noise and homomorphic processing are not directly applicable to this class of sensor data. Therefore, a minimum mean square error (MMSE) filter was designed to treat this class of sensor data. The resulting filter was implemented in an adaptive format to account for changes in local statistics and edges. A radar image processing technique which provides the MMSE estimate inside homogeneous areas and tends to preserve edge structure was the result of this study. Digitally correlated Seasat-A synthetic aperture radar (SAR) imagery was used to test the technique.
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.
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.
In initial use, the high-speed digital data acquisition systems at Langley Research Center's National Transonic Facility produced data containing unacceptably high noise levels. Described is a process whereby the contributing noise sources were identified and eliminated. The effects of 60 Hz power, system grounding, EMI/RFI, and other problems are discussed and the corrective action taken is outlined. The overall effort resulted in an improvement of greater than 5:1 in system performance. Although the report describes a system specifically used for wind tunnel data acquisition, the corrective techniques employed are generally applicable to large scale high-speed data systems where signal resolution in the low microvolts range is important.
Variance of phase error reduced. Report discusses application of "windowing" concept to improve ability of telemetry receiver to track phase of square-wave phase-modulation subcarrier signal. Concept based on setting phase-tracking signal at zero outside narrow time "windows", reducing noise energy in processed signal. Result is increase in signal-to-noise ratio in tracking loop with consequent increase in accuracy of tracking and reduction in number of errors in telemetric data.
The stringent attitude determination accuracy and faster slew maneuver requirements demanded by present-day spacecraft control systems motivate the development of recursive nonlinear filters for attitude estimation. This paper presents the second-order filter development for the estimation of attitude quaternion using three-axis gyro and star tracker measurement data. Performance comparisons have been made by computer simulation of system models and filter mechanization. It is shown that the second-order filter consistently performs better than the extended Kalman filter when the performance index of the root sum square estimation error of the quaternion vector is compared. The second-order filter identifies the gyro drift rates faster than the extended Kalman filter. The uniqueness of this algorithm is the online generation of the time-varying process and measurement noise covariance matrices, derived as a function or the process and measurement nonlinearity, respectively.
The relative performance of current methods used for estimating the phase and the frequency in LDV and phase Doppler applications in low signal to noise ratio conditions is analyzed. These methods include the Fourier analysis and the correlation techniques. Three methods that use the correlation function for frequency and phase estimations are evaluated in terms of accuracy and speed of processing. These methods include: (1) the frequency estimation using zero crossings counting of the auto-correlation function, (2) the Blackman-Tukey method, and (3) the AutoRegressive method (AR). The relative performance of these methods is evaluated and compared with the Fourier analysis method which provides the optimum performance in terms of the Maximum Likelihood (ML) criteria.
Various papers on visual information processing are presented. Individual topics addressed include: aliasing as noise, satellite image processing using a hammering neural network, edge-detetion method using visual perception, adaptive vector median filters, design of a reading test for low-vision image warping, spatial transformation architectures, automatic image-enhancement method, redundancy reduction in image coding, lossless gray-scale image compression by predictive GDF, information efficiency in visual communication, optimizing JPEG quantization matrices for different applications, use of forward error correction to maintain image fidelity, effect of peanoscanning on image compression. Also discussed are: computer vision for autonomous robotics in space, optical processor for zero-crossing edge detection, fractal-based image edge detection, simulation of the neon spreading effect by bandpass filtering, wavelet transform (WT) on parallel SIMD architectures, nonseparable 2D wavelet image representation, adaptive image halftoning based on WT, wavelet analysis of global warming, use of the WT for signal detection, perfect reconstruction two-channel rational filter banks, N-wavelet coding for pattern classification, simulation of image of natural objects, number-theoretic coding for iconic systems.
Proposed technique for production of velocity maps from sequences of photographic video images of flows seeded with small particles. In digital image velocimetry, image analyzed by digital Fourier tranformation. Process free of noise, more precise, and consumes less time. Eliminates need to process photographs, indicates directions of velocity vectors unambiguously, and offers increased dynamic ranges. Because all processing performed electronically, eventually capable of mapping flow-velocity fields in real time.
The standard approach in Digital Particle Image Velocimetry (DPIV) data processing is to use Fast Fourier Transforms to obtain the cross-correlation of two single exposure subregions, where the location of the cross-correlation peak is representative of the most probable particle displacement across the subregion. This standard DPIV processing technique is analogous to Matched Spatial Filtering, a technique commonly used in optical correlators to perform the crosscorrelation operation. Phase only filtering is a well known variation of Matched Spatial Filtering, which when used to process DPIV image data yields correlation peaks which are narrower and up to an order of magnitude larger than those obtained using traditional DPIV processing. In addition to possessing desirable correlation plane features, phase only filters also provide superior performance in the presence of DC noise in the correlation subregion. When DPIV image subregions contaminated with surface flare light or high background noise levels are processed using phase only filters, the correlation peak pertaining only to the particle displacement is readily detected above any signal stemming from the DC objects. Tedious image masking or background image subtraction are not required. Both theoretical and experimental analyses of the signal-to-noise ratio performance of the filter functions are presented. In addition, a new Symmetric Phase Only Filtering (SPOF) technique, which is a variation on the traditional phase only filtering technique, is described and demonstrated. The SPOF technique exceeds the performance of the traditionally accepted phase only filtering techniques and is easily implemented in standard DPIV FFT based correlation processing with no significant computational performance penalty. An "Automatic" SPOF algorithm is presented which determines when the SPOF is able to provide better signal to noise results than traditional PIV processing. The SPOF based optical correlation processing approach is presented as a new paradigm for more robust cross-correlation processing of low signal-to-noise ratio DPIV image data."
Trailing edge (TE) noise measurements for a NACA 63-215 airfoil model are presented, providing benchmark experimental data for a cambered airfoil. The effects of flow Mach number and angle of attack of the airfoil model with different TE bluntnesses are shown. Far-field noise spectra and directivity are obtained using a directional microphone array. Standard and diagonal removal beamforming techniques are evaluated employing tailored weighting functions for quantitatively accounting for the distributed line character of TE noise. Diagonal removal processing is used for the primary database as it successfully removes noise contaminates. Some TE noise predictions are reported to help interpret the data, with respect to flow speed, angle of attack, and TE bluntness on spectral shape and peak levels. Important findings include the validation of a TE noise directivity function for different airfoil angles of attack and the demonstration of the importance of the directivity function s convective amplification terms.
Trailing edge (TE) noise measurements for a NACA 63-215 airfoil model are presented, providing benchmark experimental data for a cambered airfoil. The effects of flow Mach number and angle of attack of the airfoil model with different TE bluntnesses are shown. Far-field noise spectra and directivity are obtained using a directional microphone array. Standard and diagonal removal beamforming techniques are evaluated employing tailored weighting functions for quantitatively accounting for the distributed line character of TE noise. Diagonal removal processing is used for the primary database as it successfully removes noise contaminates. Some TE noise predictions are reported to help interpret the data, with respect to flow speed, angle of attack, and TE bluntness on spectral shape and peak levels. Important findings include the validation of a TE noise directivity function for different airfoil angles of attack and the demonstration of the importance of the directivity function s convective amplification terms.
A concept is being explored that an optical analog of the electrical Johnson noise may be used to measure temperature independently of emissivity. The concept is that a laser beam may be modulated on reflection from a hot surface by interaction of the laser photons with the thermally agitated conduction electrons or the lattice phonons, thereby adding noise to the reflected laser beam. If the reflectance noise can be detected and quantified in a background of other noise in the optical and signal processing systems, the reflectance noise may provide a noncontact measurement of the absolute surface temperature and may be independent of the surface's emissivity.
A procedure is described for the speration of electrical noise spikes from radon vibroacoustic measurements in order to obtain a valid estimate of maximax flight spectra.
A device and method is disclosed for suppression of optical noise in an optical spatial filtering system using highly coherent light. In the disclosed embodiment, input photographic film to be processed in the system, and output photographic film to be exposed, are each mounted on lateral translation devices. During application of the coherent light for exposure of the output film, the two translation devices are moved in synchronism by a motor-driven gear and linkage assembly. The ratio of the resulting output film translation to the input film translation is equal to the magnification of the optical data processing system. The noise pattern associated with the lenses and other elements in the optical processing system remains stationary while the image-producing light moves laterally through the pattern with the output film, thus averaging out the noise effect at the output film.