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At least 325 records · Page 18

New approaches in interferometric SAR data processing

It is well established that interferometric synthetic aperture radar (SAR) images can be inverted to perform surface elevation mapping. Among the factors critical to the mapping accuracy are registration of the interfering SAR images and phase unwrapping. A novel registration algorithm is presented that determines the registration parameters through optimization. A new figure of merit is proposed that evaluates the registration result during the optimization. The phase unwrapping problem is approached through a new method involving fringe line detection. The algorithms are tested with two SEASAT SAR images of terrain near Yellowstone National Park. These images were collected on Seasat orbits 1334 and 1420, which were very close together in space, i.e., less than 100 m. The resultant elevation map is compared with the USGS digital terrain elevation model.

Lin, Qian↗

Fuzzy Set Methods for Object Recognition in Space Applications

Progress on the following four tasks is described: (1) fuzzy set based decision methodologies; (2) membership calculation; (3) clustering methods (including derivation of pose estimation parameters), and (4) acquisition of images and testing of algorithms.

Keller, James M.↗

Formulation and error analysis for a generalized image point correspondence algorithm

A Generalized Image Point Correspondence (GIPC) algorithm, which enables the determination of 3-D motion parameters of an object in a configuration where both the object and the camera are moving, is discussed. A detailed error analysis of this algorithm has been carried out. Furthermore, the algorithm was tested on both simulated and video-acquired data, and its accuracy was determined.

Shapiro, Linda↗

Two neural network algorithms for designing optimal terminal controllers with open final time

Multilayer neural networks, trained by the backpropagation through time algorithm (BPTT), have been used successfully as state-feedback controllers for nonlinear terminal control problems. Current BPTT techniques, however, are not able to deal systematically with open final-time situations such as minimum-time problems. Two approaches which extend BPTT to open final-time problems are presented. In the first, a neural network learns a mapping from initial-state to time-to-go. In the second, the optimal number of steps for each trial run is found using a line-search. Both methods are derived using Lagrange multiplier techniques. This theoretical framework is used to demonstrate that the derived algorithms are direct extensions of forward/backward sweep methods used in N-stage optimal control. The two algorithms are tested on a Zermelo problem and the resulting trajectories compare favorably to optimal control results.

Plumer, Edward S.↗

A Novel Optical/digital Processing System for Pattern Recognition

This paper describes two processing algorithms that can be implemented optically: the Radon transform and angular correlation. These two algorithms can be combined in one optical processor to extract all the basic geometric and amplitude features from objects embedded in video imagery. We show that the internal amplitude structure of objects is recovered by the Radon transform, which is a well-known result, but, in addition, we show simulation results that calculate angular correlation, a simple but unique algorithm that extracts object boundaries from suitably threshold images from which length, width, area, aspect ratio, and orientation can be derived. In addition to circumventing scale and rotation distortions, these simulations indicate that the features derived from the angular correlation algorithm are relatively insensitive to tracking shifts and image noise. Some optical architecture concepts, including one based on micro-optical lenslet arrays, have been developed to implement these algorithms. Simulation test and evaluation using simple synthetic object data will be described, including results of a study that uses object boundaries (derivable from angular correlation) to classify simple objects using a neural network.

Boone, Bradley G.↗

IUEAGN: A database of ultraviolet spectra of active galactic nuclei

In 13 years of operation, IUE has gathered approximately 5000 spectra of almost 600 Active Galactic Nuclei (AGN). In order to undertake AGN studies which require large amounts of data, we are consistently reducing this entire archive and creating a homogeneous, easy-to-use database. First, the spectra are extracted using the Optimal extraction algorithm. Continuum fluxes are then measured across predefined bands, and line fluxes are measured with a multi-component fit. These results, along with source information such as redshifts and positions, are placed in the IUEAGN relational database. Analysis algorithms, statistical tests, and plotting packages run within the structure, and this flexible database can accommodate future data when they are released. This archival approach has already been used to survey line and continuum variability in six bright Seyfert 1s and rapid continuum variability in 14 blazars. Among the results that could only be obtained using a large archival study is evidence that blazars show a positive correlation between degree of variability and apparent luminosity, while Seyfert 1s show an anti-correlation. This suggests that beaming dominates the ultraviolet properties for blazars, while thermal emission from an accretion disk dominates for Seyfert 1s. Our future plans include a survey of line ratios in Seyfert 1s, to be fitted with photoionization models to test the models and determine the range of temperatures, densities and ionization parameters. We will also include data from IRAS, Einstein, EXOSAT, and ground-based telescopes to measure multi-wavelength correlations and broadband spectral energy distributions.

Pike, G.↗

Fuel optimal control of an experimental multi-mode system

In this paper, the dynamic characteristics associated with the fuel optimal control of a harmonic oscillator are utilized in the development of a near fuel optimal feedback control strategy for spacecraft vibration suppression. In this scheme, single level thrust actuators are governed by recursive computations of the standard deviations of displacement and velocity at the actuator's locations. The algorithm was tested on an experimental structure possessing a significant number of flexible body modes. The structure's response to both single and multiple mode excitation is presented.

Redmond, J.↗

Method of separation of celestial gamma-ray bursts from solar flares

We recently discovered 217 'new' celestial gamma-ray burst candidates from the 'new' burst search of the PVO real time data base. The burst search covered the time period from September 1978 to July 1988. Sixty were confirmed by at least one other spacecraft, e.g., ISEE-3, V-II, V-12, etc. None triggered the PVO high time resolution memory. In this paper we describe a new algorithm based on the relationship between time width T(w) and hardness ratio HR, to distinguish cosmic gamma-ray bursts from solar flares without knowing the directions of the events. The algorithm was tested with 83 triggered and 60 nontriggered confirmed gamma-ray bursts and 30 confirmed solar flares from PVO.

Chuang, K. W.↗

Remote sensing cloud properties from high spectral resolution infrared observations

A technique for estimating cloud radiative properties (spectral emissivity and reflectivity) in the IR is developed based on observations at a spectral resolution of approximately 0.5/cm. The algorithm uses spectral radiance observations and theoretical calculations of the IR spectra for clear and cloudy conditions along with lidar-determined cloud-base and cloud-top pressure. An advantage of the high spectral resolution observations is that the absorption effects of atmospheric gases are minimized by analyzing between gaseous absorption lines. The technique is applicable to both ground-based and aircraft-based platforms and derives the effective particle size and associated cloud water content required to satisfy, theoretically, the observed cloud IR spectra. The algorithm is tested using theoretical simulations and applied to observations made with the University of Wisconsin's ground-based and NASA ER-2 aircraft High-Resolution Infrared Spectrometer instruments.

Smith, William L.↗

Generation of artificial helioseismic time-series

We present an outline of an algorithm to generate artificial helioseismic time-series, taking into account as much as possible of the knowledge we have on solar oscillations. The hope is that it will be possible to find the causes of some of the systematic errors in analysis algorithms by testing them with such artificial time-series.

Schou, J.↗

Analysis of high vacuum systems using SINDA'85

The theory, algorithms, and test data correlation analysis of a math model developed to predict performance of the Space Station Freedom Vacuum Exhaust System are presented. The theory used to predict the flow characteristics of viscous, transition, and molecular flow is presented in detail. Development of user subroutines which predict the flow characteristics in conjunction with the SINDA'85/FLUINT analysis software are discussed. The resistance-capacitance network approach with application to vacuum system analysis is demonstrated and results from the model are correlated with test data. The model was developed to predict the performance of the Space Station Freedom Vacuum Exhaust System. However, the unique use of the user subroutines developed in this model and written into the SINDA'85/FLUINT thermal analysis model provides a powerful tool that can be used to predict the transient performance of vacuum systems and gas flow in tubes of virtually any geometry. This can be accomplished using a resistance-capacitance (R-C) method very similar to the methods used to perform thermal analyses.

Spivey, R. A.↗

Transformation of two and three-dimensional regions by elliptic systems

Several reports are attached to this document which contain the results of our research at the end of this contract period. Three of the reports deal with our work on generating surface grids. One is a preprint of a paper which will appear in the journal Applied Mathematics and Computation. Another is the abstract from a dissertation which has been prepared by Ahmed Khamayseh, a graduate student who has been supported by this grant for the last two years. The last report on surface grids is the extended abstract of a paper to be presented at the 14th IMACS World Congress in July. This report contains results on conformal mappings of surfaces, which are closely related to elliptic methods for surface grid generation. A preliminary report is included on new methods for dealing with block interfaces in multiblock grid systems. The development work is complete and the methods will eventually be incorporated into the National Grid Project (NGP) grid generation code. Thus, the attached report contains only a simple grid system which was used to test the algorithms to prove that the concepts are sound. These developments will greatly aid grid control when using elliptic systems and prevent unwanted grid movement. The last report is a brief summary of some timings that were obtained when the multiblock grid generation code was run on the Intel IPSC/860 hypercube. Since most of the data in a grid code is local to a particular block, only a small fraction of the total data must be passed between processors. The data is also distributed among the processors so that the total size of the grid can be increase along with the number of processors. This work is only in a preliminary stage. However, one of the ERC graduate students has taken an interest in the project and is presently extending these results as a part of his master's thesis.

Mastin, C. Wayne↗

An algorithm for solving the system-level problem in multilevel optimization

A multilevel optimization approach which is applicable to nonhierarchic coupled systems is presented. The approach includes a general treatment of design (or behavior) constraints and coupling constraints at the discipline level through the use of norms. Three different types of norms are examined: the max norm, the Kreisselmeier-Steinhauser (KS) norm, and the 1(sub p) norm. The max norm is recommended. The approach is demonstrated on a class of hub frame structures which simulate multidisciplinary systems. The max norm is shown to produce system-level constraint functions which are non-smooth. A cutting-plane algorithm is presented which adequately deals with the resulting corners in the constraint functions. The algorithm is tested on hub frames with increasing number of members (which simulate disciplines), and the results are summarized.

Balling, R. J.↗

SAR terrain classifier and mapper of biophysical attributes

In preparation for the launch of SIR-C/X-SAR and design studies for future orbital SAR, a program has made considerable progress in the development of an SAR terrain classifier and algorithms for quantification of biophysical attributes. The goal of this program is to produce a generalized software package for terrain classification and estimation of biophysical attributes and to make this package available to the larger scientific community. The basic elements of the SAR (Synthetic Aperture Radar) terrain classifier are outlined. An SAR image is calibrated with respect to known system and processor gains and external targets (if available). A Level 1 classifier operates on the data to differentiate: urban features, surfaces and tall and short vegetation. Level 2 classifiers further subdivide these classes on the basis of structure. Finally, biophysical and geophysical inversions are applied to each class to estimate attributes of interest. The process used to develop the classifiers and inversions is shown. Radar scattering models developed from theory and from empirical data obtained by truck-mounted polarimeters and the JPL AirSAR are validated. The validated models are used in sensitivity studies to understand the roles of various scattering sources (i.e., surface trunk, branches, etc.) in determining net backscatter. Model simulations of sigma (sup o) as functions of the wave parameters (lambda, polarization and angle of incidence) and the geophysical and biophysical attributes are used to develop robust classifiers. The classifiers are validated using available AirSAR data sets. Specific estimators are developed for each class on the basis of the scattering models and empirical data sets. The candidate algorithms are tested with the AirSAR data sets. The attributes of interest include: total above ground biomass, woody biomass, soil moisture and soil roughness.

Ulaby, Fawwaz T.↗

Detection of Obstacles in Monocular Image Sequences

The ability to detect and locate runways/taxiways and obstacles in images captured using on-board sensors is an essential first step in the automation of low-altitude flight, landing, takeoff, and taxiing phase of aircraft navigation. Automation of these functions under different weather and lighting situations, can be facilitated by using sensors of different modalities. An aircraft-based Synthetic Vision System (SVS), with sensors of different modalities mounted on-board, complements the current ground-based systems in functions such as detection and prevention of potential runway collisions, airport surface navigation, and landing and takeoff in all weather conditions. In this report, we address the problem of detection of objects in monocular image sequences obtained from two types of sensors, a Passive Millimeter Wave (PMMW) sensor and a video camera mounted on-board a landing aircraft. Since the sensors differ in their spatial resolution, and the quality of the images obtained using these sensors is not the same, different approaches are used for detecting obstacles depending on the sensor type. These approaches are described separately in two parts of this report. The goal of the first part of the report is to develop a method for detecting runways/taxiways and objects on the runway in a sequence of images obtained from a moving PMMW sensor. Since the sensor resolution is low and the image quality is very poor, we propose a model-based approach for detecting runways/taxiways. We use the approximate runway model and the position information of the camera provided by the Global Positioning System (GPS) to define regions of interest in the image plane to search for the image features corresponding to the runway markers. Once the runway region is identified, we use histogram-based thresholding to detect obstacles on the runway and regions outside the runway. This algorithm is tested using image sequences simulated from a single real PMMW image.

Kasturi, Rangachar↗

Remote Sensing of Ocean Color in the High Arctic

With four years of NASA SeaWiFS funding I established a completely new capability and expertise for in-water optical measurements nearly from scratch and with very little optical background. My first-year budget included only capital for a profiling spectral radiometer. Over the next 30 months we conducted six cruises and collected almost 300 optical profiles in challenging environments; many were collected from 21' launches. I also changed institutions during this period: it is very disruptive to move, set up a new lab, and hire and train new people, etc. We also did not have access to NASA funds for almost a year during the move because of difficulties in subcontracting and/or transferring funds. Nevertheless, we delivered data sets from six bio-optical cruises from three high latitude regions, although only two or three cruises from two areas were promised for our SeaWiFS research. The three Canadian Arctic field programs comprise the most comprehensive high latitude bio-optical and biogeochemical data sets in existence. Optical and pigment data from all six cruises have been submitted to NASA and are being included in the algorithm development test set. Additional data are still being submitted.

Cota, G. F.↗

Analysis of Photosynthetic Rate and Bio-Optical Components from Ocean Color Imagery

Our research over the last 5 years indicates that the successful transformation of ocean color imagery into maps of bio-optical properties will require continued development and testing of algorithms. In particular improvements in the accuracy of predicting from ocean color imagery the concentration of the bio-optical components of sea as well as the rate of photosynthesis will require progress in at least three areas: (1) we must improve mathematical models of the growth and physiological acclimation of phytoplankton; (2) we must better understand the sources of variability in the absorption and backscattering properties of phytoplankton and associated microparticles; and (3) we must better understand how the radiance distribution just below the sea surface varies as a function sun and sky conditions and inherent optical properties.

Kiefer, Dale A.↗