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We present a neural network algorithm for spectroscopic retrievals of concentrations of trace gases. Using synthetic data we demonstrate that a neural network is well suited for filtering etalon fringes and provides superior performance to conventional least squares minimization techniques. This novel method can improve the accuracy of atmospheric retrievals and minimize biases.
Empirical mode decomposition is an adaptive signal processing method that when applied to a broadband signal, such as that generated by turbulence, acts as a set of band-pass filters. This process was applied to data from time-resolved, particle image velocimetry measurements of subsonic jets prior to computing the second-order, two-point, space-time correlations from which turbulent phase velocities and length and time scales could be determined. The application of this method to large sets of simultaneous time histories is new. In this initial study, the results are relevant to acoustic analogy source models for jet noise prediction. The high frequency portion of the results could provide the turbulent values for subgrid scale models for noise that is missed in large-eddy simulations. The results are also used to infer that the cross-correlations between different components of the decomposed signals at two points in space, neglected in this initial study, are important.
Empirical mode decomposition is an adaptive signal processing method that when applied to a broadband signal, such as that generated by turbulence, acts as a set of band-pass filters. This process was applied to data from time-resolved, particle image velocimetry measurements of subsonic jets prior to computing the second-order, two-point, space-time correlations from which turbulent phase velocities and length and time scales could be determined. The application of this method to large sets of simultaneous time histories is new. In this initial study, the results are relevant to acoustic analogy source models for jet noise prediction. The high frequency portion of the results could provide the turbulent values for subgrid scale models for noise that is missed in large-eddy simulations. The results are also used to infer that the cross-correlations between different components of the decomposed signals at two points in space, neglected in this initial study, are important.
Empirical mode decomposition is an adaptive signal processing method that when applied to a broadband signal, such as that generated by turbulence, acts as a set of band-pass filters. This process was applied to data from time-resolved, particle image velocimetry measurements of subsonic jets prior to computing the second-order, two-point, space-time correlations from which turbulent phase velocities and length and time scales could be determined. The application of this method to large sets of simultaneous time histories is new. In this initial study, the results are relevant to acoustic analogy source models for jet noise prediction. The high frequency portion of the results could provide the turbulent values for subgrid scale models for noise that is missed in large-eddy simulations. The results are also used to infer that the cross-correlations between different components of the decomposed signals at two points in space, neglected in this initial study, are important.
A temperature-sensitive coating, based on hematite (iron III oxide), has been developed to measure surface temperature using spectral techniques. The hematite powder is added to a binder that allows the mixture to be painted on the surface of a test specimen. The coating dynamically changes its relative spectral makeup or color with changes in temperature. The color changes from a reddish-brown appearance at room temperature (25 C) to a black-gray appearance at temperatures around 600 C. The color change is reversible and repeatable with temperature cycling from low to high and back to low temperatures. Detection of the spectral changes can be recorded by different sensors, including spectrometers, photodiodes, and cameras. Using a-priori information obtained through calibration experiments in known thermal environments, the color change can then be calibrated to yield accurate quantitative temperature information. Temperature information can be obtained at a point, or over an entire surface, depending on the type of equipment used for data acquisition. Because this innovation uses spectrophotometry principles of operation, rather than the current methods, which use photoluminescence principles, white light can be used for illumination rather than high-intensity short wavelength excitation. The generation of high-intensity white (or potentially filtered long wavelength light) is much easier, and is used more prevalently for photography and video technologies. In outdoor tests, the Sun can be used for short durations as an illumination source as long as the amplitude remains relatively constant. The reflected light is also much higher in intensity than the emitted light from the inefficient current methods. Having a much brighter surface allows a wider array of detection schemes and devices. Because color change is the principle of operation, the development of high-quality, lower-cost digital cameras can be used for detection, as opposed to the high-cost imagers needed for intensity measurements with the current methods. Alternative methods of detection are possible to increase the measurement sensitivity. For example, a monochrome camera can be used with an appropriate filter and a radiometric measurement of normalized intensity change that is proportional to the change coating temperature. Using different spectral regions yields different sensitivities and calibration curves for converting intensity change to temperature units. Alternatively, using a color camera, a ratio of the standard red, green, and blue outputs can be used as a self-referenced change. The blue region (less than 500 nm) does not change nearly as much as the red region (greater than 575 nm), so a ratio of color intensities will yield a calibrated temperature image. The new temperature sensor coating is easy to apply, is inexpensive, can contour complex shape surfaces, and can be a global surface measurement system based on spectrophotometry. The color change, or relative intensity change, at different colors makes the optical detection under white light illumination, and associated interpretation, much easier to measure and interpret than in the detection systems of the current methods.
A method is described for combined interpolation and enhancement of ERTS multispectral scanner data sets. Previous research has shown that good enhancement is most easily achieved when there are a large number of data points contained within the radius of gyration of the system point spread function. This requirement can be met using ERTS data by interpolating the data before enhancement. By varying the interpolation scale factor the data set can be empirically matched to a precalculated optimum restoration filter. Once the proper match of data and filter has been found the enhancement can be carried out directly or the enhancement and interpolation operations can be combined into a single filter thereby greatly reducing the processing time. Experimental results of applying this technique are shown along with more conventional methods of image interpolation and enlargement.
Additional insight is provided into the use of the Doyle-Stein (1979, 1981) technique in aeroelastic control problems by examining the application of the method to a flutter control problem. The system to be controlled consists of a full-size wind tunnel model of a wing, plus an aileron, an actuator, and an accelerometer used to sense the motion of the wing. A full-state feedback controller was designed using linear optimal control theory, and a Kalman filter was used in the feedback loop for state estimation. The filter design procedure is explained along with that to improve closed-loop properties of the system. The locus of the poles of the filter is examined as a scalar design parameter is varied. The Doyle-Stein design procedure is shown to substantially improve the stability properties of an active flutter controller designed using the linear quadratic Gaussian control theory.
Several techniques for modeling the disturbances to a spacecraft's attitude caused by moving crew members are presented. These disturbances can be the largest moments acting on a manned spacecraft, and knowledge of their effect is important in the sizing, design, and analysis/simulation of spacecraft attitude control systems. The modeling techniques are identified as two principal types: deterministic and stochastic. Three techniques of each type are presented. The deterministic models include point-mass motion derivatives and a discussion on dynamic models of moving crew members. The stochastic techniques are highlighted by a Fourier transform method and the representation of long-term crew disturbance activities as outputs from appropriately designed filters. A z-transform technique is developed to obtain a difference-equation form of stochastic models for use on digital computers. An appendix derives spacecraft equations of motion which can be used with many of the models discussed.
Launch vehicle effluent (LVE) monitoring is part of NASA's overall tropospheric and stratospheric environmental program. Following nine techniques are evaluated and developed in report: bubbler method, pH measurements, indicator tubes, microcoulometers, modified condensation nuclei counter, dual-isotope absorption, gas-filter correlation, chemiluminescent nitric oxide detection, chemiluminescent luminol-oxidation detection.
It is pointed out that the effects of delays of less than 100 msec in visual displays on pilot dynamic response and system performance are of particular interest at this time because improvements in the latest computer-generated imagery (CGI) systems are expected to reduce CGI displays delays to this range. Attention is given to data which quantify the effects of display delays in the range of 0-100 msec on system stability and performance, and pilot dynamic response for a particular choice of aircraft dynamics, display, controller, and task. The conventional control system design methods are reviewed, the pilot response data presented, and data for long delays, all suggest lead filter compensation of display delay. Pilot-aircraft system crossover frequency information guides compensation filter specification.
The analysis scheme and meteorological applications of the GEMPAK data analysis and display software system developed by NASA are described. The program was devised to permit objective, versatile, and practical analysis of satellite meteorological data using a minicomputer and a display system with graphics capability. A data area can be selected within the data file for the globe, and data-sparse regions can be avoided. Distances between observations and the nearest observation points are calculated in order to avoid errors when determining synoptic weather conditions. The Barnes (1973) successive correction method is employed to restore the amplitude of small yet resolvable wavelengths suppressed in an initial filtering pass. The rms deviation is then calculated in relation to available measured data. Examples are provided of treatment of VISSR data from the GOES satellite and a study of the impact of incorrect cloud height data on synoptic weather field analysis.
Different kinds of inteference may cause problems to the proper detection and analysis of the atmospheric signals, when using VHF and UHF radars. These are separated into passive and active contributions. Passive contributions are existent in the receiving system without the radar transmitter switched on. Active contributions are due to scatter and reflection of the own transmitted radar signal from unwanted targets, which are called clutter. Of major importance to radar systems are active interference contributions. Different methods can be applied for elimination or at least suppressing unwanted effects. These are; (1) Directional filtering, i.e., applying optimum suppression of antenna sidelobes, (2) Range filtering, i.e., suppressing unwanted signals only in affected range gates, (3) selection by amplitude distributions, (4) Temporal filtering, i.e., recognizing typical temporal variations of the clutter signals, through spectral characteristics, and applying matched filters.
The invention relates to an apparatus and associated methods for the optical recognition and tracking of multiple objects in real time. Multiple point spatial filters are employed that pre-define the objects to be recognized at run-time. The system takes the basic technology of a Vander Lugt filter and adds a hololens. The technique replaces time, space and cost-intensive digital techniques. In place of multiple objects, the system can also recognize multiple orientations of a single object. This later capability has potential for space applications where space and weight are at a premium.
Various lidar methods have been developed for measuring the atmospheric temperature, making use of the temperature dependant characteristics of rotational Raman scattering (RRS) from nitrogen and oxygen, and Rayleigh or Rayleigh-Brillowin scattering (RS or RBS). These methods have various advantages and disadvantages as compared to each other but their potential accuracies are principal characteristics of their efficiency. No systematic attempt has been undertaken so far to compare the efficiences, in the above meaning, of different temperature lidar methods. Two RRS techniques have been compared. Here, we do such a comparison using two methods based on the detection and analysis of RS (RBS) spectra. Four methods are considered here for measuring the atmospheric temperature. One of them (Schwiesow and Lading, 1981) is based on an analysis of the RS linewidth with two Michelson interferometers (MI) in parallel. The second method (Shimisu et al., 1986) employs a high-resolution analysis of the RBS line shape. The third method (Cooney, 1972) employs the temperature dependance of the RRS spectrum envelope. The fourth method (Armstrong, 1974) makes use of a scanning Fabry-Perot interferometer (FPI) as a comb filter for processing the periodic RRS spectrum of the nitrogen. Let us denote the corresponding errors in measuring the temperature by sigma(sub MI), sigma(sub HR), sigma(sub ENV), and sigma(sub FPI). Let us also define the ratios chi(sub 1) = sigma(sub MI)/sigma(sub ENV), chi(sub 2) = sigma(sub HR)/sigma(sub ENV), and chi(sub 3) = sigma(sub FPI)/sigma(sub ENV) interpreted as relative errors with respect to sigma(sub ENV).
A technique is developed which demonstrates how to interpret a large fully-populated filter gain matrix as a set of scalar gains. The inverse problem is also solved, namely, how to develop a large-order filter gain matrix from a specified set of scalar gains. Examples are given to illustrate the method.
This paper presents an iterative Linear Quadratic Gaussian (LQG) controller design approach for a linear stochastic system with an uncertain open-loop model and unknown noise statistics. This approach consists of closed-loop identification and controller redesign cycles. In each cycle, the closed-loop identification method is used to identify an open-loop model and a steady-state Kalman filter gain from closed-loop input/output test data obtained by using a feedback LQG controller designed from the previous cycle. Then the identified open-loop model is used to redesign the state feedback. The state feedback and the identified Kalman filter gain are used to form an updated LQC controller for the next cycle. This iterative process continues until the updated controller converges. The proposed controller design is demonstrated by numerical simulations and experiments on a highly unstable large-gap magnetic suspension system.
Global monitoring by satellites is important for many types of environmental studies. Among these, the wind field is the single most important atmospheric state variable required for understanding atmospheric motion and predicting weather. Studies indicate that a global determination of the tropospheric wind field to an accuracy of 1-5 m/sec is critical for improved numerical weather forecasting. This measurement could be carried out with a spaceborne lidar system sensing the Doppler shift of a laser signal backscattered from the atmosphere. Over the past four years we have developed a ground-based Edge Technique lidar system and demonstrated wind measurements through the troposphere with high accuracy (1-6 m/s) and high spatial resolution. Recently, we began the design of a shuttle based wind measurement system for technology demonstration as part of the Zephyr program. In this paper, we present the characteristics of the high spectral resolution etalon filter technology for lidar wind measurement with the Edge Technique. In conclusion, a spacecraft motion compensation method has been discussed. We demonstrated experimentally that the etalon can be tuned to compensate for any satellite induced Doppler shift to an accuracy of better than 0.6 m/s over a time period of 2.5 ms.
Speech intelligibility was evaluated using a virtual acoustic ("3-D audio") display using the method specified by ANSI. Ten subjects were evaluated with stimuli either unfiltered or low-pass filtered at 4 kHz. Results show virtual acoustic techniques are advantageous for both full-bandwidth (44.1 kHz srate) and low (8 kHz srate) bandwidth "telephone-grade" teleconferencing systems.