BACKGROUND: Alzheimer's disease is a multifactorial disorder that may be diagnosed earlier using a combination of tests rather than any single test. Search algorithms and optimization techniques in combination with model evaluation techniques have been used previously to perform the selection of suitable feature sets. Previously we successfully applied GA with LR to neuropsychological data contained within the The Australian Imaging, Biomarkers and Lifestyle (AIBL) study of aging, to select cognitive tests for prediction of progression of AD. This research addresses an Adaptive Genetic Algorithm (AGA) in combination with LR for identifying the best biomarker combination for prediction of the progression to AD. RESULTS: The model has been explored in terms of parameter optimization to predict conversion from healthy stage to AD with high accuracy. Several feature sets were selected - the resulting prediction moddels showed higher area under the ROC values (0.83-0.89). The results has shown consistency with some of the medical research reported in literature. CONCLUSION: The AGA has proven useful in selecting the best combination of biomarkers for prediction of AD progression. The algorithm presented here is generic and can be extended to other data sets generated in projects that seek to identify combination of biomarkers or other features that are predictive of disease onset or progression.

BACKGROUND: Assessment of risk and early diagnosis of Alzheimer's disease (AD) is a key to its prevention or slowing the progression of the disease. Previous research on risk factors for AD typically utilizes statistical comparison tests or stepwise selection with regression models. Outcomes of these methods tend to emphasize single risk factors rather than a combination of risk factors. However, a combination of factors, rather than any one alone, is likely to affect disease development. Genetic algorithms (GA) can be useful and efficient for searching a combination of variables for the best achievement (eg. accuracy of diagnosis), especially when the search space is large, complex or poorly understood, as in the case in prediction of AD development. RESULTS: Multiple sets of neuropsychological tests were identified by GA to best predict conversions between clinical categories, with a cross validated AUC (area under the ROC curve) of 0.90 for prediction of HC conversion to MCI/AD and 0.86 for MCI conversion to AD within 36 months. CONCLUSIONS: This study showed the potential of GA application in the neural science area. It demonstrated that the combination of a small set of variables is superior in performance than the use of all the single significant variables in the model for prediction of progression of disease. Variables more frequently selected by GA might be more important as part of the algorithm for prediction of disease development.

UNLABELLED: NetRaVE is a small suite of R functions for generating dependency networks using sparse regression methods. Such networks provide an alternative to interpreting 'top n lists' of genes arising out of an analysis of microarray data, and they provide a means of organizing and visualizing the resulting information in a manner that may suggest relationships between genes. AVAILABILITY: NetRaVE is freely available for academic use and has been tested in R 2.10.1 under Windows XP, Linux and Mac OS X. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The design, error budget, and preliminary test results of a 50-56-GHz synthetic aperture radiometer demonstration system are presented. The instrument consists of a fixed 24-element array of correlation interferometers and is capable of producing calibrated images with 1deg spatial resolution within a 17deg wide field of view. This system has been built to demonstrate a performance and a design which can be scaled to a much larger geostationary Earth imager. As a baseline, such a system would consist of about 300 elements and would be capable of providing contiguous full hemispheric images of the Earth with 1 K of radiometric precision and 50-km spatial resolution. An error budget is developed around this goal and then tested with the demonstrator system. Errors are categorized as either scaling (i.e., complex gain) or additive (noise and bias) errors. Sensitivity to gain and/or phase error is generally proportional to the magnitude of the expected visibility, which is high only in the shortest baselines of the array, based on model simulations of the Earth as viewed from geostationary Earth orbit. Requirements range from approximately 0.5% and 0.3deg of amplitude and phase uncertainty, respectively, for the closest spacings at the center of the array, to about 4% and 2.5deg for the majority of the array. The latter requirements are demonstrated with our instrument using relatively simple references and antenna models, and by relying on the intrinsic stability and efficiency of the system. The 0.5% requirement (for the short baselines) is met by measuring the detailed spatial response (e.g., on the antenna range) and by using an internal noise diode reference to stabilize the response. This result suggests a hybrid image synthesis algorithm in which long baselines are processed by a fast Fourier transform and the short baselines are processed by a more precise (G-matrix) algorithm which can handle small anomalies among antenna and receiver responses. Visibility biases and other additive errors must be below about 1.5 mK on average, regardless of baseline. The bias requirement is largely met with a phase-shifting scheme applied to the local oscillator distribution of our demonstration system. Low mutual coupling among the horn antennas of our design is also critical to minimize the biases caused by crosstalk of receiver noise. Performance is validated by a three-way comparison between interference fringes measured on the antenna range, solar transit observations, and the system model.

The NASA Earth Science System Pathfinder (ESSP) mission Aquarius, will measure global ocean surface salinity with ~120 km spatial resolution every 7-days with an average monthly salinity accuracy of 0.2 psu (parts per thousand) [1]. This requires an L-band low-noise radiometer with the long-term calibration stability of les0.15 K over 7 days. The instrument utilizes a push-broom configuration which makes it impractical to use a traditional warm load and cold plate in front of the feedhorns. Therefore, to achieve the necessary performance Aquarius utilizes a Dicke radiometer with noise injection to perform a warm - hot calibration. The radiometer sequence between antenna, Dicke load, and noise diode has been optimized to maximize antenna observations and therefore minimize NEDT. This is possible due the ability to thermally control the radiometer electronics and front-end components to 0.1degCrms over 7 days.

A geophysical model function (GMF), relating the directional response of polarimetric brightness temperatures to ocean surface winds, is developed for the WindSat multifrequency polarimetric microwave radiometer. This GMF is derived from the WindSat data and tuned with the aircraft radiometer measurements for very high winds from the Hurricane Ocean Wind Experiment in 1997. The directional signals in the aircraft polarimetric radiometer data are corroborated by coincident Ku-band scatterometer measurements for wind speeds in the range of 20-35 m/s. We applied an iterative retrieval algorithm using the polarimetric brightness temperatures from 18-, 23-, and 37-GHz channels. We find that the root-mean-square direction difference between the Global Data Assimilation System winds and the closest WindSat wind ambiguity is less than 20/spl deg/ for above 7-m/s wind speed. The retrieval analysis supports the consistency of the Windrad05 GMF with the WindSat data.

The spectral window at L-band (1.413 GHz) is important for passive remote sensing of surface parameters such as soil moisture and sea surface salinity that are needed to understand the hydrological cycle and ocean circulation. Radiation from celestial sources (mostly galactic) is strong in this window, and an accurate accounting of this background radiation is often needed for calibration. This paper presents a comparison of the background radiation predicted by a model developed from modern radio astronomy measurements with measurements made with several modern L-band remote sensing radiometers. The comparison validates the model and illustrates the magnitude of the correction necessary in remote sensing applications.

Geo STAR represents a new approach to microwave atmospheric sounding that is now under development. It has capabilities similar to sensors currently operating on low earth orbiting weather satellites but is intended for deployment in geostationary orbit - where it will complement future infrared sounders and enable all-weather temperature and humidity soundings and rain mapping. The required spatial resolution of 50 km or better dictates an aperture of 4 meters or more at a sounding frequency of 50 GHz, which is difficult to achieve with a real aperture system - this is the reason why it has until now not been possible to put a microwave sounder on a geostationary platform, GeoSTAR is instead based on a synthetic aperture imaging approach. Among the advantages of such a system are that there are no moving parts, and the size of the aperture is easily expandable to meet future needs. A ground based prototype of GeoSTAR is currently under development in an effort led by the Jet Propulsion Laboratory

The development of a microstrip-based L-band Dicke radiometer with the long-term stability required for future ocean salinity measurements to an accuracy of 0.1 psu is presented. This measurement requires the L-band radiometers to have calibration stabilities of les 0.05 K over 2 days. This research has focused on determining the optimum radiometer requirements and configuration to achieve this objective. System configuration and component performance have been evaluated with radiometer test beds at both JPL and GSFC. The GSFC test bed uses a cryogenic chamber that allows long-term characterization at radiometric temperatures in the range of 70 - 120 K. The research has addressed several areas including component characterization as a function of temperature and DC bias, system linearity, optimum noise diode injection calibration, and precision temperature control of components. A breadboard radiometer, utilizing microstrip-based technologies, has been built to demonstrate this long-term stability

Preliminary details of a 2-D synthetic aperture radiometer prototype operating from 50 to 55 GHz will be presented. The laboratory prototype is being developed to demonstrate the technologies and system design needed to do millimeter-wave atmospheric soundings with high spatial resolution from Geostationary orbit. The concept is to deploy a large thinned aperture Y-array on a geostationary satellite, and to use aperture synthesis to obtain images of the Earth without the need for a large mechanically scanned antenna. The laboratory prototype consists of a Y-array of 24 horn antennas, MMIC receivers, and a digital cross-correlation subsystem

Radiation from the celestial sky in the spectral window at 1.413 GHz is strong and an accurate accounting of this background radiation is needed for calibration and retrieval algorithms. Modern radio astronomy measurements in this window have been converted into a brightness temperature map of the celestial sky at L-band suitable for such applications. This work presents a comparison of the background predicted by this map with the measurements of several modern L-band remote sensing radiometers.

A future mission for a new microwave atmospheric temperature sounder radiometer in a middle Earth orbit (MEO) at 11,000 km altitude is described. The MeoSTAR design uses a stationary 1-dimensional Synthetic Thinned Array Radiometer in the 50-60 GHz microwave sounding band, to provide a "pushbroom" image as the satellite orbits. The advantage of this concept is an image with a high spatial resolution and a wide swath with no scanning antenna to disturb the visual and IR sensors on the same satellite

Global mapping of near surface ocean wind vectors is crucial for many oceanographic and atmospheric studies. The US Navy together with the National Polar Orbiting Environmental Satellite System (NPOESS) launched the WindSat with multifrequency polarimetric radiometers in January 2003 to demonstrate the passive polarimetry for large spatial coverage of ocean surface wind vector measurements from space. We derived the geophysical model function (GMF) for Windsat polarimetric brightness temperature measurements using six months of matchup dataset. The Windsat GMF was compared with the aircraft radiometer and radar measurements and the SeaWinds scatterometer winds with good agreement up to about 20 m/s wind speed

In this paper, the problem of combined target model estimation and position-based visual servoing is addressed. The target object is assumed to be stationary with at least 3 distinguishable feature points. The midpoint triangulation method and a rough estimation method are developed for initial estimation of the target model and relative pose of target in current end-effector frame. A novel decoupled EKF-based online estimation algorithm is proposed to improve the target model and relative pose estimation simultaneously under continuous robot dynamic motion. This new method is robust to large initial estimation errors and provides consistent and accurate target model estimation for optimal pose estimation as required in position-based visual servoing. Experimental results are given to demonstrate the performance of the proposed method.

L-band radiometer brightness temperature measurements of a saltwater pond were made as a function of salinity and temperature. A precision L-band radiometer with stability better than 0.1 K per day was used for these measurements. The L-band measurements are in good agreement with three dielectric constant models over a temperature range from 8/spl deg/C to 32/spl deg/C and a salinity range from 25-40 psu. Based on this experiment, these dielectric models will provide an excellent basis for the algorithm development and design of the future National Aeronautics and Space Administration Aquarius satellite mission.

An NEDT analysis of a Dicke radiometer with noise diode injection is presented. The analysis is formulated for a calibration that would form separate running averages of receiver noise temperature and of gain in order to minimize the NEDT and maximize the antenna observation duty cycle relative to the reference and noise diode duty cycles. Results are applied to the Aquarius ocean salinity radiometer problem to show that near ideal total-power radiometer performance is possible.

Ocean salinity measurements using the Passive Active L/S-band instrument flying on the NCAR C-130 aircraft were made in July 2002 near Monterey, CA. When the radiometer data were corrected for the SST using the Klein and Swift salinity model and surface roughness effects using the L-band scatterometer, the retrieved salinity measurements had an RMS difference of 0.2-0.3 psu when compared with the R/V Point Sur ship measured salinity data.

Sea surface salinity is a key parameter for the study of ocean circulation, global water cycle and hence climate changes. In response to these measurement needs, Aquarius was selected recently for the third NASA Earth System Science Pathfinder (ESSP) Announcement of Opportunity for a planned launch date in September 2008. The characteristics of the Aquarius instrument are provided in this paper.

The development of a compact, lightweight, dual-frequency antenna feed for future soil moisture and sea surface salinity (SSS) missions is described. The design is based on the microstrip stacked-patch array (MSPA) to be used to feed large lightweight deployable rotating mesh antenna for spaceborne L-band (/spl sim/ 1 GHz) passive and active sensing systems. This paper describes the design of a single-element stacked patch element and the 7-element array configuration.

In this paper, the dynamic performance of position-based visual servoing methods in the Cartesian and image spaces are investigated. Two major classifications of the position-based method are analyzed. For motion control defined in the stationary desired end-effector frame, the shortest straight line Cartesian trajectory can be achieved, but the corresponding image trajectories are not controlled and may leave the camera field of view. For motion control defined in the moving current end-effector frame, the straight line Cartesian trajectory is not guaranteed, however, the im- age trajectories can be indirectly controlled in this method to move approximately along straight lines when the commanded orientation is small. Simulation results are given to compare the Cartesian and image trajectories of various implementations of the position-based method with those of the image-based and 2 1/2-D methods.

This paper presents a theoretical comparison of the stability and robustness of the two basic visual servoing methods, image-based and position-based visual servoing. A common framework for comparison based on the energy shaping plus damping injection methodology is presented. Previous stability results for the image-based method are extended to show the robustness of stability with respect to camera and target modeling, errors. Similar stability and robustness analyses are extended to the analysis of the position-based method. It is shown that both methods are locally asymptotically stable and robust with respect to camera and target modeling errors. However the stability boundary with respect to above errors has not been established.

This paper examines the use of shared control in performing part assembly operations with a telerobotic system. The shared control is based on the combination of operator commands and a local autonomous visual servo controller. This shared visual control permits partial automation of the telerobotic operations improving accuracy and allowing the operator to concentrate on high level decision making. The design of the methodology and experimental results of an assembly operation are presented.

L and S-band radiometer brightness temperature measurements from a salt-water pond were made of as a function of salinity and temperature. The L-band measurements are in excellent agreement with the Klein and Swift salinity model, and will provide accurate predictions for the L-band emission from the ocean for future ocean salinity satellite missions.

In this paper, hybrid motion control and planning strategies for image constraints avoidance in robot visual servoing are presented. The proposed methods consist of a local switching control method and a global hybrid trajectory planning method. In local switching control, image local minima and image singularities can both be resolved by hybrid image-based and position-based visual servoing. The global hybrid trajectory planner is based on the artificial potential field method and various Cartesian and image constraints are incorporated. Based on the proposed methods, motion planning for image boundaries and image local minima avoidance is considered in this paper. Experimental and simulation results are given to demonstrate the efficiency of the proposed methods.

Data were acquired by the Passive and Active L- and S-band airborne sensor (PALS) during the 1999 Southern Great Plains (SGP99) experiment in Oklahoma to study remote sensing of soil moisture in vegetated terrain using low-frequency microwave radiometer and radar measurements. The PALS instrument measures radiometric brightness temperature and radar backscatter at L- and S-band frequencies with multiple polarizations and approximately equal spatial resolutions. The data acquired during SGP99 provide information on the sensitivities of multichannel low-frequency passive and active measurements to soil moisture for vegetation conditions including bare, pasture, and crop surface cover with field-averaged vegetation water contents mainly in the 0-2.5 kg m/sup -2/ range. Precipitation occurring during the experiment provided an opportunity to observe wetting and drying surface conditions. Good correlations with soil moisture were observed in the radiometric channels. The 1.41-GHz horizontal-polarization channel showed the greatest sensitivity to soil moisture over the range of vegetation observed. For the fields sampled, a radiometric soil moisture retrieval accuracy of 2.3% volumetric was obtained. The radar channels showed significant correlation with soil moisture for some individual fields, with greatest sensitivity at 1.26-GHz vertical copolarized channel. However, variability in vegetation cover degraded the radar correlations for the combined field data. Images generated from data collected on a sequence of flight lines over the watershed region showed similar patterns of soil moisture change in the radiometer and radar responses. This indicates that under vegetated conditions for which soil moisture estimates may not be feasible using current radar algorithms, the radar measurements nevertheless show a response to soil moisture change, and they can provide useful information on the spatial and temporal variability of soil moisture. An illustration of the change detection approach is given.

Experimental data are presented to support the development of a new concept for ocean wind velocity measurement (speed and direction) with the polarimetric microwave radar technology. This new concept has strong potential for improving the wind direction accuracy and extending the useful swath width by up to 30% for follow-on NASA spaceborne scatterometer mission to SeaWinds series. The key issue is whether there is a relationship between the polarization state of ocean backscatter and surface wind velocity at NASA scatterometer frequencies (13 GHz). An airborne Ku-band polarimetric scatterometer (POLSCAT) was developed for proof-of-concept measurements. A set of aircraft flights indicated repeatable wind direction signals in the POLSCAT observations of sea surfaces at 9-11 m/s wind speed. The correlation coefficients between co- and cross-polarized radar response of ocean surfaces have a peak-to-peak amplitude of about 0.4 and are shown to have an odd-symmetry with respect to the wind direction, unlike the normalized radar cross sections.

A passive/active WS-band (PALS) microwave aircraft instrument to measure ocean salinity and soil moisture has been built and tested. Because the L-band brightness temperatures associated with salinity changes are expected to be small, it was necessary to build a very sensitive and stable system. This new instrument has dual-frequency, dual polarization radiometer and radar sensors. The antenna is a high beam efficiency conical horn. The PALS instrument was installed on the NCAR C-130 aircraft and soil moisture measurements were made in support of the Southern Great Plains 1999 experiment in Oklahoma from July 8-14, 1999. Data taken before and after a rainstorm showed significant changes in the brightness temperatures, polarization ratios and radar backscatter, as a function of soil moisture. Salinity measurement missions were flown on July 17-19, 1999, southeast of Norfolk, VA, over the Gulf Stream. The measurements indicated a clear and repeatable salinity signal during these three days, which was in good agreement with the Cape Hatteras ship salinity data. Data were also taken in the open ocean and a small decrease of 0.2 K was measured in the brightness temperature, which corresponded to the salinity increase of 0.4 psu measured by the M/V Oleander vessel.

A set of geophysical error sources for the microwave remote sensing of ocean surface salinity have been examined. The error sources include the sea surface temperature, sea surface roughness, atmospheric gases, ionospheric Faraday rotation, and solar and Galactic emission sources. It is shown that the brightness temperature effects of a few kelvin can be expected for most of these error sources. The key correction requirements for accurate salinity measurements are the knowledge accuracy of 0.5/spl deg/C for the sea surface temperature (SST), 10 mbar for the surface air pressure, 2/spl deg/C for the surface air temperature, 0.20 accuracy for the Faraday rotation, and surface roughness equivalent to 0.3 m s/sup -1/ for the surface wind speed. We suggest the use of several data products for corrections, including the AMSR-type instruments for SST and liquid cloud water, the AMSU-type product for air temperature, the scatterometer products or numerical weather analysis for the air pressure, coincidental radar observations with 0.2 dB precision for surface roughness, and on-board polarimetric radiometer channel for Faraday rotation. The most significant sky radiation is from the Sun. A careful design of the antenna is necessary to minimize the leakage of solar radiation or reflection into the antenna sidelobes. The narrow-band radiation from Galactic hydrogen clouds with a bandwidth of less than 1 MHz is also significant, but can be corrected with a radio sky survey or minimized with a notched (band-rejection) filter centered at 1.421 GHz. The other planetary and Galactic radio sources can also be flagged with a small data loss. We have performed a sampling analysis for a polar-orbiting satellite with 900 km swath width to determine the number of satellite observations over a given surface grid cell during an extended period. Under the assumption that the observations from different satellite passes are independent, it is suggested that an accuracy of 0.1 psu (practical salinity unit) is achievable for global monthly 10 latitude by 10 longitude gridded products.

Microwave radiometry and scatterometry are established techniques for surface remote sensing applications. Some applications, such as measurement of sea surface salinity (SSS), sea surface temperature (SST), and soil moisture, require low frequency observations (/spl sim/6 GHZ and below) for good sensitivity, and sensors with large antennas to achieve adequate spatial resolution. Potentially, benefits can be obtained by observing simultaneously with passive and active channels, at similar frequencies, viewing angles, and spatial resolutions, making use of the complementary information contained in the emissivity and backscattering signatures of land and ocean targets. In this study, the authors investigate a concept for combined passive and active multichannel sensing with high spatial resolution, high measurement sensitivity, and wide swath for frequent global coverage. The system consists of a lightweight, relating, deployable mesh antenna with offset feeds. The system specifications are designed primarily for the measurement of sea surface salinity, since this application drives the precision and calibration requirements and, like soil moisture, is a science measurement for which no spaceborne capability currently exists. Demonstration of a capability for sea surface salinity will enhance the potential of this large antenna concept for other applications such as soil moisture and, by including higher frequencies, high resolution measurements of ocean winds, precipitation, sea-surface temperature, and sea-ice.

A spaceborne inflatable antenna concept is evaluated for passive microwave sensing of soil moisture and ocean salinity. The concept makes use of a large-diameter, offset-fed, parabolic-torus antenna with multiple feeds in a conical pushbroom configuration. An inflatable structure provides the means for deploying the large-aperture, low-mass, and low-cost antenna system in space, suitable for operation in the 1-3-GHz frequency range needed for soil moisture and salinity sensing. The concept is designed to provide multichannel, constant-incidence-angle, wide-swath, and high-radiometric-precision observations of the Earth's surface. These capabilities facilitate estimation of soil moisture and salinity, with global coverage every two to three days. Simulations show that a 25-m diameter, 1.41- and 2.69-GHz, dual-polarized system should be capable of providing surface soil moisture estimates with an accuracy of /spl sim/0.04 g-cm/sup -3/ (where vegetation water content is less than /spl sim/5 kg-m/sup -2/) at a spatial resolution of /spl sim/30 km. Although inflatable systems represent a new and untested technology for remote-sensing applications, the advantages of low packaged volume, low manufacturing cost, and low mass provide an incentive for their study. This paper evaluates one possible concept for incorporating the capabilities of inflatable systems into a scientific mission and for demonstrating these capabilities for remote-sensing applications.

The sensitivities of wind direction signals in passive microwave brightness temperatures of sea surfaces to wind speed, incidence angle, polarization, and frequency are presented in this paper. The experimental data were acquired from a series of aircraft flights from 1993 through 1996 by the Jet Propulsion Laboratory (JPL) using JPL 19 and 37 GHz polarimetric radiometers (WINDRAD). Fourier analysis of the data versus mind direction was carried out and the coefficients of Fourier series are illustrated against the wind speed at 45/spl deg/, 55/spl deg/, and 65/spl deg/ incidence angles. There is a good agreement between the JPL aircraft flight data and Wentz's Special Sensor Microwave/Imager (SSM/I) geophysical model function for the vertically polarized brightness temperatures, but Wentz's SSM/I wind direction model for horizontal polarization shows a significantly stronger upwind and downwind asymmetry than the aircraft flight data. Comparison of the dual-frequency WINDRAD data show's that the wind direction signals are similar at 19 and 37 GHz, although the 37 GHz data have slightly stronger signals than the 19 GHz data. In general, the azimuthal variations of brightness temperatures increase with increasing wind speed from low to moderate winds, then level off and decrease at high minds. The only exception is the U measurements at 65/spl deg/ incidence angle, which have a stronger than expected signal at low winds. An exponential function was proposed to model the sensitivities of wind direction signals to wind speeds. The coefficients of the empirical model are provided in this paper and are useful for the simulation of ocean brightness temperatures and for the development of geophysical retrieval algorithms.

Vision based grasping holds great promise for grasping in dynamic environments where the object and/or robot are moving. The paper introduces a grasp planning approach for visual servo controlled robots with a single camera mounted at the end effector. Sensory control, mechanical, and geometrical issues in the design of such an automatic grasp planner are discussed and the corresponding constraints are highlighted. In particular, the integration of visual feature selection constraints is emphasized. Some quality measures are introduced to rate the candidate grasps. The grasp planning strategy and implementation issues in the development of an automatic grasp planner (AGP) are described. Simulation and experimental results are presented to verify the correctness of the approach and its effectiveness in dealing with dynamic situations.

The NASA/JPL Airborne Rain MApping Radar (ARMAR) was operated on the NASA DC-8 aircraft during TOGA COARE in early 1993. On 12 flights ARMAR observed stratiform precipitation associated with mesoscale convective systems. The statistics of 16 melting layer parameters, including maximum reflectivity, cooling rate, Doppler velocity, LDR, and the HH-VV correlation coefficient are presented and discussed.

Dual-frequency (19 and 37 GHz), multi-incidence measurements of the Stokes parameters of sea surface microwave emission are reported. A series of aircraft polarimetric radiometer flights were carried out over the National Data Buoy Center (NDBC) moored buoys deployed off the northern California coast in July and August 1994. Measured radiometric temperatures showed a few Kelvin azimuth modulations in all Stokes parameters with respect to the wind direction. Wind directional signals observed in the 37-GHz channel were similar to those in the 19-GHz channel. This indicates that the wind direction signals in sea surface brightness temperatures have a weak frequency dependence in the range of 19-37 GHz. Harmonic coefficients of the wind direction signals were derived from experimental data versus incidence angle. It was found that the first harmonic coefficients, which are caused by the up and downwind asymmetric surface features, had a small increasing trend with the incidence angle. In contrast, the second harmonic coefficients, caused by the up and crosswind asymmetry, showed significant variations in T/sub v/ and U data, with a sign change when the incidence angle increased from 45/spl deg/ to 65/spl deg/. Besides the first three Stokes parameters, the fourth Stokes parameter, V, which had never been measured before for sea surfaces, was measured using our 19-GHz channel. The Stokes parameter V. Has an odd symmetry just like that of the third Stokes parameter U, and increases with increasing incidence angles. In summary, sea surface features created by surface winds are anisotropic in azimuth direction and modulate all Stokes parameters of sea surface microwave brightness temperatures by as large as a few Kelvin in the range of incidence angles from 45/spl deg/ to 65/spl deg/ applicable to spaceborne observations.

The problem of automatically selecting the image features is an important aspect of visual servoing systems. This paper addresses the main issues relevant to automatic features selection in the context of visual servoing. The constraints imposed by the task, the feature extraction and state estimation processes are derived. The quality measures are formulated and a features selection strategy is introduced. In addition to the features selection, the proposed methodology provides the automatic selection of windows for the target features during the servoing. Also it can be applied for optimal vision sensor positioning. The design and implementation of an automatic CAD-based features selector (AFS) using the proposed methodology has been achieved. The experimental results are presented to demonstrate the effectiveness and correctness of the proposed framework.

This paper presents the design of a Cartesian space LQR controller for full three dimensional position based visual servoing. It is shown that by designing the controller in Cartesian space, the design process can be greatly simplified if the LQR cost function is selected appropriately. Experimental results which demonstrate the significant improvements in system performance obtained with this design method are also presented.

This paper presents a complete design methodology for Cartesian position based visual servo control for robots with a single camera mounted at the end-effector. Position based visual servo control requires the explicit calculation of the relative position and orientation (POSE) of the workpiece object with respect to the camera. This is accomplished using image plane measurements of a number of known feature points on the object, and then applying an extended Kalman filter to obtain a recursive solution of the photogrammetric equations, and to properly combine redundant measurements. The control is then designed by specifying the desired trajectories with respect to the object and forming the control error in the end-effector frame. The implementation using a distributed computer architecture is described. An experimental system has been built and used to evaluate the performance of the POSE estimation and the position based visual servo control. Several results for relative trajectory control and target tracking are presented. Results of the experiments showing the effect of loss of some of the redundant features are also presented.

Presents the first experimental evidence that the polarimetric brightness temperatures of sea surfaces are sensitive to ocean wind direction in the incidence angle range of 30 to 50/spl deg/. The experimental data were collected by a K-band (19.35 GHz) polarimetric wind radiometer (WINDRAD) mounted on the NASA DC-8 aircraft. A set of aircraft radiometer flights was successfully completed in November 1993. The authors performed circle flights over National Data Buoy Center (NDBC) moored buoys deployed off the northern California coast, which provided ocean wind measurements. The results indicate that passive polarimetric radiometry has a strong potential for global ocean wind speed and direction measurements from space.>

This paper deals with the integration of a real-time trajectory planner and neural network (CMAC) based controller with on-line learning for robotic manipulators in the presence of obstacles. The effectiveness of the integrated system is verified by simulations for the first two links of the Adept-One robot.>

Pulse compression allows a substantial reduction in the peak transmitted power of a radar and is attractive for spaceborne remote sensing applications. In the case of a downward looking rain measuring radar, however, the range sidelobes associated with surface return can mask return from rain and must be kept to a minimum. The authors describe the pulse compression system for the NASA/JPL Airborne Rain Mapping Radar. This system uses time-domain weighting of the transmitted pulse and is able to achieve a range sidelobe level of -55 dB or better in flight tests. This is significantly lower than other values reported in the open literature.>

A vision-based position sensing system which provides three-dimensional relative position and orientation (pose) of an arbitrary moving object with respect to a camera for a real-time tracking control is studied. Kalman filtering was applied to vision measurements for the implicit solution of the photogrametric equations and to provide significant temporal filtering of the resulting motion parameters resulting in optimal pose estimation. Both computer simulation and real-time experimental results are presented to verify the effectiveness of the Kalman filter approach with large vision measurement noise.>

The development of a control strategy for direct dynamic end-point control of a manipulator based on position estimates obtained from endpoint mounted sensors is presented. The feasibility of using an extended Kalman filter algorithm for relative position estimates based on task object feature locations extracted from images obtained from an end-point mounted camera has been studied. An experimental system has been constructed and the position estimation and control strategy implemented to test the performance of the design. Tests have demonstrated the successful operation of the control strategy developed and have also demonstrated the feasibility of using an extended Kalman filter for relative position estimates at a sample rate of 61 Hz.>