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At least 325 records · Page 18

Improving Surface PM2.5 Forecasts in the United States Using an Ensemble of Chemical Transport Model Outputs: 2. Bias Correction with Satellite Data for Rural Areas

This work serves as the second of a two-part study to improve surface PM2.5 forecasts in the continental U.S. through the integrated use of multi satellite aerosol optical depth (AOD) products (MODIS Terra/Aqua and VIIRS DT/DB), multichemical transport model (CTM) (GEOS-Chem, WRF-Chem, and CMAQ) outputs, and ground observations. In Part I of the study, an ensemble Kalman filter (KF) technique using three CTM outputs and ground observations was developed to correct forecast bias and generate a single best forecast of PM2.5 for next day over non rural areas that have surface PM2.5 measurements in the proximity of 125 km. Here, with AOD data, we extended the bias correction into rural areas where the closest air quality monitoring station is at least 125–300 km away. First, we ensembled all of satellite AOD products to yield the single best AOD. Second, we corrected daily PM2.5 in rural areas from multiple models through the AOD spatial pattern between these areas and non rural areas, referred to as “extended ground truth” or EGT, for the present day. Lastly, we applied the KF technique to reduce the forecast bias for next day using the EGT. Our results find that the ensemble of bias-corrected daily PM2.5 from three CTMs for both today and next day show the best performance. Together, the two-part study develops a multimodel and multi-AOD bias-correction technique that has the potential to improve PM2.5 forecasts in both rural and non rural areas in near real time, and be readily implemented at state levels.

Huanxin Zhang↗

Maximizing the Volume of Collocated Data from Two Coordinated Suborbital Platforms

Suborbital (e.g., airborne) campaigns that carry advanced remote sensing and in situ payloads provide detailed observations of atmospheric processes, but can be challenging to use when it is necessary to geographically collocate data from multiple platforms that make repeated observations of a given geographic location at different altitudes. This study reports on a data collocation algorithm that maximizes the volume of collocated data from two coordinated suborbital platforms and demonstrates its value using data from the NASA Aerosol Cloud Meteorology Interactions Over the western Atlantic Experiment (ACTIVATE) suborbital mission. A robust data collocation algorithm is critical for the success of the ACTIVATE mission goal to develop new and improved remote sensing algorithms, and quantify their performance. We demonstrate the value of these collocated data to quantify the performance of a recently developed vertically resolved lidar + polarimeter–derived aerosol particle number concentration (Na ) product, resulting in a range-normalized mean absolute deviation (NMAD) of 9% compared to in situ measurements. We also show that this collocation algorithm increases the volume of collocated ACTIVATE data by 21% compared to using only nearest-neighbor finding algorithms alone. Additional to the benefits demonstrated within this study, the data files and routines produced by this algorithm have solved both the critical collocation and the collocation application steps for researchers who require collocated data for their own studies. This freely available and open-source collocation algorithm can be applied to future suborbital campaigns that, like ACTIVATE, use multiple platforms to conduct coordinated observations, e.g., a remote sensing aircraft together with in situ data collected from suborbital platforms.

Atmosphere↗

3D Display Using Conjugated Multiband Bandpass Filters

Stereoscopic display techniques are based on the principle of displaying two views, with a slightly different perspective, in such a way that the left eye views only by the left eye, and the right eye views only by the right eye. However, one of the major challenges in optical devices is crosstalk between the two channels. Crosstalk is due to the optical devices not completely blocking the wrong-side image, so the left eye sees a little bit of the right image and the right eye sees a little bit of the left image. This results in eyestrain and headaches. A pair of interference filters worn as an optical device can solve the problem. The device consists of a pair of multiband bandpass filters that are conjugated. The term "conjugated" describes the passband regions of one filter not overlapping with those of the other, but the regions are interdigitated. Along with the glasses, a 3D display produces colors composed of primary colors (basis for producing colors) having the spectral bands the same as the passbands of the filters. More specifically, the primary colors producing one viewpoint will be made up of the passbands of one filter, and those of the other viewpoint will be made up of the passbands of the conjugated filter. Thus, the primary colors of one filter would be seen by the eye that has the matching multiband filter. The inherent characteristic of the interference filter will allow little or no transmission of the wrong side of the stereoscopic images.

Bae, Youngsam↗

Absorption Filter Based Optical Diagnostics in High Speed Flows

Two major regimes where laser light scattered by molecules or particles in a flow contains significant information about the flow are Mie scattering and Rayleigh scattering. Mie scattering is used to obtain only velocity information, while Rayleigh scattering can be used to measure both the velocity and the thermodynamic properties of the flow. Now, recently introduced (1990, 1991) absorption filter based diagnostic techniques have started a new era in flow visualization, simultaneous velocity and thermodynamic measurements, and planar velocity measurements. Using a filtered planar velocimetry (FPV) technique, we have modified the optically thick iodine filter profile of Miles, et al., and used it in the pressure-broaden regime which accommodates measurements in a wide range of velocity applications. Measuring velocity and thermodynamic properties simultaneously, using absorption filtered based Rayleigh scattering, involves not only the measurement of the Doppler shift, but also the spectral profile of the Rayleigh scattering signal. Using multiple observation angles, simultaneous measurement of one component velocity and thermodynamic properties in a supersonic jet were measured. Presently, the technique is being extended for simultaneous measurements of all three components of velocity and thermodynamic properties.

Samimy, Mo↗

Nonlinear filter design

A technique for identifying nonlinear systems was introduced, beginning with a single input-single output system. Assuming the system is initially at rest, the first kernel (first convolution integral in the continuous case or first convolution sum in the discrete case) was calculated. A controllable and observable linear realization was then obtained in a particular canonical form. The actual nonlinear system was probed with an appropriate input (or inputs) and the output (or outputs) determined. For the linear system, the input was computed that produces the same output. In the difference between the inputs to the nonlinear and linear systems, basic information was found about the nonlinear system. There is an interesting class of nonlinear systems for which this type of identification scheme should prove to be accurate.

Hunt, L. R.↗

Sensor failure detection system

Advanced concepts for detecting, isolating, and accommodating sensor failures were studied to determine their applicability to the gas turbine control problem. Five concepts were formulated based upon such techniques as Kalman filters and a screening process led to the selection of one advanced concept for further evaluation. The selected advanced concept uses a Kalman filter to generate residuals, a weighted sum square residuals technique to detect soft failures, likelihood ratio testing of a bank of Kalman filters for isolation, and reconfiguring of the normal mode Kalman filter by eliminating the failed input to accommodate the failure. The advanced concept was compared to a baseline parameter synthesis technique. The advanced concept was shown to be a viable concept for detecting, isolating, and accommodating sensor failures for the gas turbine applications.

Beattie, E. C.↗

Recursive Robot-Arm Dynamics via Filtering and Smoothing

Forward and inverse dynamics solved using Kalman filtering and Bryson-Frazier smoothing. Dynamics of serial-link robot arm solved by using recursive techniques from linear filtering and smoothing theory. Solutions of dynamical equations give forces, moments, and accelerations at joints between links, and multilink inertia matrix and its inverse. Theoretical developments lay foundation for use of filtering and smoothing techniques in design of robot controls.

Rodriguez, Guillermo↗

Astronomical imaging by filtered weighted-shift-and-add technique

The weighted-shift-and-add speckle imaging technique is analyzed using simple assumptions. The end product is shown to be a convolution of the object with a typical point-spread function (psf) that is similar in shape to the telescope psf and depends marginally on the speckle psf. A filter can be applied to each data frame before locating the maxima, either to identify the speckle locations (matched filter) or to estimate the instantaneous atmospheric psf (Wiener filter). Preliminary results show the power of the technique when applied to photon-limited data and to extended objects.

Ribak, Erez↗

Multiscale Morphological Filtering for Analysis of Noisy and Complex Images

Images acquired with passive sensing techniques suffer from illumination variations and poor local contrasts that create major difficulties in interpretation and identification tasks. On the other hand, images acquired with active sensing techniques based on monochromatic illumination are degraded with speckle noise. Mathematical morphology offers elegant techniques to handle a wide range of image degradation problems. Unlike linear filters, morphological filters do not blur the edges and hence maintain higher image resolution. Their rich mathematical framework facilitates the design and analysis of these filters as well as their hardware implementation. Morphological filters are easier to implement and are more cost effective and efficient than several conventional linear filters. Morphological filters to remove speckle noise while maintaining high resolution and preserving thin image regions that are particularly vulnerable to speckle noise were developed and applied to SAR imagery. These filters used combination of linear (one-dimensional) structuring elements in different (typically four) orientations. Although this approach preserves more details than the simple morphological filters using two-dimensional structuring elements, the limited orientations of one-dimensional elements approximate the fine details of the region boundaries. A more robust filter designed recently overcomes the limitation of the fixed orientations. This filter uses a combination of concave and convex structuring elements. Morphological operators are also useful in extracting features from visible and infrared imagery. A multiresolution image pyramid obtained with successive filtering and a subsampling process aids in the removal of the illumination variations and enhances local contrasts. A morphology-based interpolation scheme was also introduced to reduce intensity discontinuities created in any morphological filtering task. The generality of morphological filtering techniques in extracting information from a wide variety of images obtained with active and passive sensing techniques is discussed. Such techniques are particularly useful in obtaining more information from fusion of complex images by different sensors such as SAR, visible, and infrared.

Kher, A.↗

Recursive Inversion Of Externally Defined Linear Systems

Technical memorandum discusses mathematical technique described in "Recursive Inversion by Finite-Impulse-Response Filters" (ARC-12247). Technique is recursive algorithm yielding finite-impulse-response approximation of unknown single-input/single-output, causal, time-invariant, linear, real system, response of which is sequence of impulses. Useful in such diverse applications as medical diagnoses, identification of military targets, geophysical exploration, and nondestructive testing.

Bach, Ralph E., Jr.↗

Generation of random hypersurfaces.

A technique to generate multidimensional random hypersurfaces with given statistical properties numerically on a digital computer is discussed in this paper. The technique is based on the linear filter theory. Using this technique, two-dimensional random surfaces are generated to illustrate the procedure. Statistics of these two-dimensional random surfaces are presented. Possible applications of these random surfaces in various physical problems are discussed.

Youakim, M. Y.↗

Direct and Inverse Techniques of Guided-Mode Resonance Filters Designs

Guided-mode resonances arise in single or multilayer waveguides where one or more homogeneous layers are replaced by diffraction gratings (Fig. 1.) The diffractive element enables an electromagnetic wave incident on a waveguide grating to be coupled to the waveguide modes supportable by the structure in the absence of the modulation (i.e. the difference between the high and low dielectric constants of the grating) at specific values of the wavelength and incident angle. The periodic modulation of the guide makes the structure leaky, preventing sustained propagation of modes in the waveguide and coupling the waves out into the substrate and cover. As the wavelength is varied around resonance a rapid variation in the intensities of the external propagating waves occurs. By selecting a grating period small enough to eliminate the higher-order propagating waves, an increase in the zero-order intensities up to 100% can result. The pronounced frequency selectivity of guided-mode resonances in dielectric waveguide gratings can be applied to design high-efficiency reflection and transmission filters [1-3].

Tibuleac, Sorin↗

Improved Technique for Finding Vibration Parameters

Filtering and sample manipulation reduce noise effects. Analysis technique improves extraction of vibrational frequencies and damping rates from measurements of vibrations of complicated structure. Structural vibrations measured by accelerometers. Outputs digitized at frequency high enough to cover all modes of interest. Use of method on set of vibrational measurements from Space Shuttle, raised level of coherence from previous values below 50 percent to values between 90 and 99 percent

Andrew, L. V.↗

Designing A Microwave Band-Stop Filter

Lumped-circuit design techniques applied to iris-coupled cavities. Waveguide/cavity filter imitates lumped series and parallel combinations of inductance and capacitance over narrow stopband centered at 7.190 GHz. Filter made of standard WR125 waveguide stock.

Manshadi, F.↗

Satellite stratospheric aerosol measurement validation

The validity of the stratospheric aerosol measurements made by the satellite sensors SAM II and SAGE was tested by comparing their results with each other and with results obtained by other techniques (lider, dustsonde, filter, and impactor). The latter type of comparison required the development of special techniques that convert the quantity measured by the correlative sensor (e.g. particle backscatter, number, or mass) to that measured by the satellite sensor (extinction) and quantitatively estimate the uncertainty in the conversion process. The results of both types of comparisons show agreement within the measurement and conversion uncertainties. Moreover, the satellite uncertainty is small compared to aerosol natural variability (caused by seasonal changes, volcanoes, sudden warmings, and vortex structure). It was concluded that the satellite measurements are valid.

Russell, P. B.↗

Satellite stratospheric aerosol measurement validation

The validity of the stratospheric aerosol measurements made by the satellite sensors SAM II and SAGE was tested by comparing their results with each other and with results obtained by other techniques (lider, dustsonde, filter, and impactor). The latter type of comparison required the development of special techniques that convert the quantity measured by the correlative sensor (e.g., particle backscatter, number, or mass) to that measured by the satellite sensor (extinction) and quantitatively estimate the uncertainty in the conversion process. The results of both types of comparisons show agreement within the measurement and conversion uncertainties. Moreover, the satellite uncertainty is small compared to aerosol natural variability (caused by seasonal changes, volcanoes, sudden warmings, and vortex structure). It was concluded that the satellite measurements are valid.

Russell, P. B.↗

Optimal Tuner Selection for Kalman-Filter-Based Aircraft Engine Performance Estimation

An emerging approach in the field of aircraft engine controls and system health management is the inclusion of real-time, onboard models for the inflight estimation of engine performance variations. This technology, typically based on Kalman-filter concepts, enables the estimation of unmeasured engine performance parameters that can be directly utilized by controls, prognostics, and health-management applications. A challenge that complicates this practice is the fact that an aircraft engine s performance is affected by its level of degradation, generally described in terms of unmeasurable health parameters such as efficiencies and flow capacities related to each major engine module. Through Kalman-filter-based estimation techniques, the level of engine performance degradation can be estimated, given that there are at least as many sensors as health parameters to be estimated. However, in an aircraft engine, the number of sensors available is typically less than the number of health parameters, presenting an under-determined estimation problem. A common approach to address this shortcoming is to estimate a subset of the health parameters, referred to as model tuning parameters. The problem/objective is to optimally select the model tuning parameters to minimize Kalman-filterbased estimation error. A tuner selection technique has been developed that specifically addresses the under-determined estimation problem, where there are more unknown parameters than available sensor measurements. A systematic approach is applied to produce a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. Tuning parameter selection is performed using a multi-variable iterative search routine that seeks to minimize the theoretical mean-squared estimation error of the Kalman filter. This approach can significantly reduce the error in onboard aircraft engine parameter estimation applications such as model-based diagnostic, controls, and life usage calculations. The advantage of the innovation is the significant reduction in estimation errors that it can provide relative to the conventional approach of selecting a subset of health parameters to serve as the model tuning parameter vector. Because this technique needs only to be performed during the system design process, it places no additional computation burden on the onboard Kalman filter implementation. The technique has been developed for aircraft engine onboard estimation applications, as this application typically presents an under-determined estimation problem. However, this generic technique could be applied to other industries using gas turbine engine technology.

Simon, Donald L.↗