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Systems for making automatic noise figure measurements of millimeter wave mixers have been developed using both analog and digital techniques. The effect of IF mismatch on the measured noise figures is also determined with these methods (Forsythe, 1982). The measurement systems are versatile enough to be used to measure the noise figure of receivers anywhere from 30 to 300 GHz.
Here, this paper studies Tikhonov regularization (ridge regression) parameter selection for problems in vibrations and acoustics. The selection method is based on a popular Bayesian method, but it incorporates measurements of sensor noise. The regularization parameter is closely related to the ratio of system input energy to noise energy, so noise measurements inform the inference procedure and improve parameter identification. In cases where standard Bayesian regularization identifies zero as the optimal regularization parameter, noise measurements guarantee a unique nonzero optimum. Sufficient theoretical criteria are developed for this guarantee. The method is verified in even-determined and under-determined configurations in an acoustic source localization simulation and a vibration load identification experiment. It is shown to yield significant improvements over existing empirical Bayesian regularization. Improvements are larger in the even-determined case and smaller in the under-determined case, wherein the inverse solution is less sensitive to the regularization parameter.
Measurements of noise produced by a model of a wheel well (rectangular cavity), landing gear (wheel and strut), and flap at Mach numbers of 0.18 and 0.40 have been made in an anechoic flow facility. Individual component noise and component interference noise are described in terms of the OASPL, spectra, and streamwise or flyover directivity patterns. Areas of significant sound generation are illuminated and causes of these noise sources are suggested. Results from an acoustic imaging technique are used to point out other source regions not discernible by simple far-field measurements.
An experimental study of the noise resulting from the interaction of an airfoil with incident turbulence is presented. The test models include NACA0015 airfoils of different chord lengths, a flat plate with a sharp leading edge, and an airfoil of same section as a reference Fowler flap. The airfoils are immersed in nearly isotropic turbulence. Two approaches for performing the noise measurements are used and compared. The effects that turbulence intensity and scales, airfoil geometry, velocity and angle of attack have on the incident turbulence interaction noise are examined. Detailed directivity measurements are presented. It is found that noise spectral levels beyond the peak frequency decrease more with decreasing airfoil leading edge sharpness, and that spectral peak level (at 0 deg. angle of attack) appears to be mostly controlled by the airfoil fs thickness and chord. Increase in turbulence scale and intensity are observed to lead to a uniform increase of the noise spectral levels with an LI(sup 2) dependence (where L is the turbulence longitudinal integral scale and I is the turbulence intensity). Noise levels are found to scale with the 6th power of velocity and the 2nd power of the airfoil chord. Sensitivity to changes in angle of attack appears to have a turbulence longitudinal integral scale to chord (C) ratio dependence, with large effects on noise for L/C greater than or equal to 1 and decreased effects as L/C becomes smaller than 1. For all L/C values, the directivity pattern of the noise resulting from the incident turbulence is seen to remain symmetric with respect to the direction of the mean flow until stall, at which point, the directivity becomes symmetric with respect to the airfoil chord. It is also observed that sensitivity to angle of attack changes is more pronounced on the model suction side than on the model pressure side, and in the higher frequency range of the spectra for the largest airfoils tested (L/C less than 0.24).
Measurement and analysis of radio frequency indigenous noise
Development of noise measurement units for airport and aircraft noise reduction and psychoacoustic studies
Optimum length buffer crystals are used with an amplification section for measuring the noise figure for acoustic amplifiers. Measuring the time required to saturate with noise a signal, which is reflected back and forth in the circuit, gives a direct measurement of the amplifiers noise figure.
Radiometric microwave noise temperature measurements were used to estimate atmospheric transmission loss. The following lumped element model expression is used for the noise temperature contribution, T double prime = T sub p (1 - 1/L). This relationship is used to estimate the transmission loss L in terms of T double prime and the atmosphere effective physical temperature T sub p. This report evaluates T sub p in terms of assumed distributed loss and temperature models. Simplified expressions are presented for low loss applications. For these applications L was determined directly and accurately without integration or iteration.
The noise from perfectly expanded coaxial jets was measured in an anechoic chamber for different operating conditions with the same total thrust, mass flow, and exit area. The shape of the measured noise spectrum at different angles to the jet axis was found to agree with spectral shapes for single, axisymmetric jets. Based on these spectra, the sound was characterized as being generated by large turbulent structures or fine-scale turbulence. Modeling the large scale structures as instability waves, a stability analysis was conducted for the coaxial jets to identify the growing and decaying instability waves in each shear layer and predict their noise radiation pattern outside the jet. When compared to measured directivity, the analysis identified the region downstream of the outer potential core, where the two shear layers were merging, as the source of the peak radiated noise where instability waves, with their origin in the inner shear layer, reach their maximum amplitude. Numerical computations were also performed using a linearized Euler equation solver. Those results were compared to both the results from the instability wave analysis and to measured data.
Noise transmission measurements were made for a 0.020-inch panel with and without air flow on its surface. Tests were conducted with both an absorbent and reverberant chamber behind the panel. Panel stresses for some of these tests were also determined. Noise spectra obtained inside the absorbent chamber with flow attached and flow not attached to the panel appeared to contain several peaks corresponding in frequency to panel vibration modes. These peaks were notably absent when the chamber was reverberant. The noise reduction through the test panel measured with the aid of an absorbent chamber for the flow-not-attached case is in general agreement with values predicted by the theoretical weight law, which assumes negligible panel stiffness. Corresponding data for the flow-attached case do not follow the weight law but rather indicate less noise reduction at the high frequencies. The main stress responses of the panel without air flow occurred at its fundamental vibration mode. In the presence of air flow the main response occurs in a vibration mode having a node line perpendicular to the direction of air flow.
There is a need for feedback control of the large flexible space structures which are going to be increasingly important in the future of the space program. These structures are very lightly damped, and vibrations may persist for a long time when the system is disturbed unless an active feedback control strategy is used to damp out the vibrations. The system is best described by a partial differential equation description, but the more common approach is to use a large set of second order differential equations, where a large number of modes must be retained if the mathematics is to provide an adequate description of the dynamical process. Sensors, such as accelerometers and rate gyros, may provide data to the feedback controller so that it may respond appropriately to control the system. The data from the sensors is not perfect, but is subject to noise, called measurement noise, and the dynamical process itself is subject to disturbances referred to as process noise. Filtering the sensor signals to remove the measurement noise, and using the resulting state estimates to control the system are investigated.
The ability of feed-forward neural network architectures to learn continuous valued mappings in the presence of noise was demonstrated in relation to parameter identification and real-time adaptive control applications. An error function was introduced to help optimize parameter values such as number of training iterations, observation time, sampling rate, and scaling of the control signal. The learning performance depended essentially on the degree of embodiment of the control law in the training data set and on the degree of uniformity of the probability distribution function of the data that are presented to the net during sequence. When a control law was corrupted by noise, the fluctuations of the training data biased the probability distribution function of the training data sequence. Only if the noise contamination is minimized and the degree of embodiment of the control law is maximized, can a neural net develop a good representation of the mapping and be used as a neurocontroller. A multilayer net was trained with back-error-propagation to control a cart-pole system for linear and nonlinear control laws in the presence of data processing noise and measurement noise. The neurocontroller exhibited noise-filtering properties and was found to operate more smoothly than the teacher in the presence of measurement noise.
Extensive antenna-noise temperature measurements at 1.6 GHz (L-band) were made using a 1.2 m (4 ft. diameter) parabolic dish antenna mounted on the flying bridge of a modern 15,690-ton, commercial-container ship. Both in-harbor and at-sea radiometer measurements were made that indicated a steady background, antenna-noise temperature value slightly less than 70 degrees Kelvin (K) at elevation angles of 5 percent, and greater, at 1.6 GHz. A comparison of theoretical and measured values indicate excellent agreement within about 5K for at-sea data. These measurements are helpful to RF equipment designers of maritime, L-band shipboard terminals for operation with the two, geostationary, maritime satellites, Marisat-A and -B.
Careful consideration must be given to data acquisition and analysis techniques in the design of experiments for the measurement of noise generated by flight vehicles. Although noise measurement locations and data reduction procedures are specified for aircraft certification by FAA and ICAO directives, for example, there are virtually no established procedures for aircraft noise measurement for other purposes. To optimize the quality and quantity of information obtained in a flight acoustics experiment, microphone layout, data acquisition, and analysis must be tailored to the specific test objective. This paper will review flight acoustics technology at NASA Langley Research Center developed over the past decade. In particular, the paper will focus on flight experiments performed for three diverse objectives: (1) research applications, such as noise prediction code validation, (2) noise impact modeling, and (3) noise abatement flight procedures. To best achieve these diverse objectives, different deployments of microphone systems on the ground are required, and different data analysis techniques are needed. In all cases, accurate positioning of the aircraft synchronized in time with the data recording is necessary. However, there are some restrictions on flight operations unique to each case for the methods to properly work.
Efficient version of maximum-likelihood algorithm devised for calculating normal-mode frequencies and damping parameters of vibrating system from experimental data where both process noise and measurement noise present. Method applicable in vibration analysis of such complicated structures as vehicles, aircraft, and spacecraft. New algorithm simplification of existing maximum-likelihood formulation using Kalman filter that allows for both process and measurement noise.
A development of the in plane open loop rotational equations of motion for the proposed Spacecraft Control Laboratory Experiment (SCOLE) in orbit configuration is presented based on an Eulerian formulation. The mast is considered to be a flexible beam connected to the (rigid) shuttle and the reflector. Frequencies and mode shapes are obtained for the mast vibrational appendage modes (assumed to be decoupled) for different boundary conditions based on continuum approaches and also preliminary results are obtained using a finite element representation of the mast reflector system. The linearized rotational in plane equation is characterized by periodic coefficients and open loop system stability can be examined with an application of the Floquet theorem. Numerical results are presented to illustrate the potential instability associated with actuator time delays even for delays which represent only a small fraction of the natural period of oscillation of the modes contained in the open loop model of the system. When plant and measurement noise effects are added to the previously designed deterministic model of the hoop column system, it is seen that both the system transient and steady state performance are degraded. Mission requirements can be satisfied by appropriate assignment of cost function weighting elements and changes in the ratio of plant noise to measurement noise.
An overview is given of a comprehensive approach to filter and dynamics modeling for attitude determination error analysis. The models presented include both batch least-squares and sequential attitude estimation processes for both spin-stabilized and three-axis stabilized spacecraft. The discussion includes a brief description of a dynamics model of strapdown gyros, but it does not cover other sensor models. Model parameters can be chosen to be solve-for parameters, which are assumed to be estimated as part of the determination process, or consider parameters, which are assumed to have errors but not to be estimated. The only restriction on this choice is that the time evolution of the consider parameters must not depend on any of the solve-for parameters. The result of an error analysis is an indication of the contributions of the various error sources to the uncertainties in the determination of the spacecraft solve-for parameters. The model presented gives the uncertainty due to errors in the a priori estimates of the solve-for parameters, the uncertainty due to measurement noise, the uncertainty due to dynamic noise (also known as process noise or measurement noise), the uncertainty due to the consider parameters, and the overall uncertainty due to all these sources of error.
NASA sets aggressive, strategic, civil aircraft performance and environmental goals and develops ambitious technology roadmaps to guide its research efforts. NASA has adopted a phased approach for community noise reduction of civil aircraft. While the goal of the near-term first phase focuses primarily on source noise reduction, the goal of the second phase relies heavily on presumed architecture changes of future aircraft. The departure from conventional airplane configurations to designs that incorporate some type of propulsion noise shielding is anticipated to provide an additional 10 cumulative EPNdB of noise reduction. One candidate propulsion system for these advanced aircraft is the open rotor engine. In some planned applications, twin open rotor propulsors are located on the aft fuselage, with the vehicle s empennage shielding some of their acoustic signature from observers on the ground. This study focuses on predicting the noise certification benefits of a notional open rotor aircraft with tail structures shielding a portion of the rotor noise. The measured noise of an open rotor test article--collected with and without an acoustic barrier wall--is the basis of the prediction. The results are used to help validate NASA s reliance on acoustic shielding to achieve the second phase of its community noise reduction goals. The noise measurements are also compared to a popular empirical diffraction correlation often used at NASA to predict acoustic shielding.