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During the FIRE Cirrus IFO II, a set of passive radiometers were deployed at the Coffeyville, Kansas, Hub, site B, to compliment the Radiation Measurement System (RAMS) on board the NASA ER-2 and NCAR Sabreliner. The following three instruments were used at the surface: Narrow-field-of View IR Radiometer (NFOV); Total-Direct-Diffuse Radiometer (TDDR); and Near-Infrared Spectroradiometer (NIRS).
The feasibility of detecting the cold core of the wake vortex from the wingtips of an aircraft using a passive microwave radiometer was investigated. It was determined that there is a possibility that a cold core whose physical temperature drop is 10 C or greater and which has a diameter of 5 m or greater can be detected by a microwave radiometer. The radiometer would be a noise injection balanced Dicke radiometer operating at a center frequency of 60 GHz. It would require a noise figure of 5 dB, a predetection bandwidth of 6 GHz, and an integration time of 2 seconds resulting in a radiometric sensitivity of 0.018 K. However, three additional studies are required. The first would determine what are the fluctuations in the radiometric antenna temperature due to short-term fluctuations in atmospheric pressure, temperature, and relative humidity. Second, what is the effect of the pressure and temperature drop within the cold core of the wake vortex on its opacity. The third area concerns the possibility of developing a 60 GHz radiometer with a radio metric sensitivity an order of magnitude improvement over the existing state of the art.
In this paper, we compare dry-snow extinction coefficients derived from radar altimeter data with brightness temperature data from passive microwave measurements over a portion of the East Antarctic plateau. The comparison between the extinction coefficients and the brightness temperatures shows a strong negative correlation, where the correlation coefficients ranged from -0.87 to -0.95. The extinction coefficient of the dry polar snow decreases with increasing surface elevation, while the average brightness temperature increases with surface elevation. Our analysis shows that the observed trends are related to geographic variations in scattering coefficient of snow, which in turn are controlled by variations in surface temperature and snow accumulation rate. By combining information present in the extinction coefficient and brightness temperature data sets, we develop a model that can be used to obtain quantitative estimates of the accumulation rate of dry polar snow.
The visual display expected to be generated by a Passive Millimeter Wave (PMMW) camera and sensor system has been simulated on a Silicon Graphics IRIS workstation at the NASA Langley Research Center (LaRC). The low resolution of the sensor has been simulated by graphically manipulating the scene as it is being drawn by the IRIS in real time. Camera field of view, sensor resolution, and sensor update rate are the controllable parameters. Physical effects such as lens model, radome effects, and noise have not been included at this time. An approximate dynamic model of the atmospheric phenomenology has been included which generates the gray-scale intensity values in real time for the simulated image. The gray-scale values are proportional to temperature. A snapshot capability which captures individual image frames during real-time operation has been included. These images were used to validate the approximate phenomenology model against a more rigorous physical model.
This paper describes a new technique of passive ranging which is based on utilizing the image-plane expansion experienced by every object as its distance from the sensor decreases. This technique belongs in the feature/object-based family. The motion and shape of a small window, assumed to be fully contained inside the boundaries of some object, is approximated by an affine transformation. The parameters of the transformation matrix are derived by initially comparing successive images, and progressively increasing the image time separation so as to achieve much larger triangulation baseline than currently possible. Depth is directly derived from the expansion part of the transformation. To a first approximation, image-plane expansion is independent of image-plane location with respect to the focus of expansion (FOE) and of platform maneuvers. Thus, an expansion-based method has the potential of providing a reliable range in the difficult image area around the FOE. In areas far from the FOE the shift parameters of the affine transformation can provide more accurate depth information than the expansion alone, and can thus be used similarly to the way they have been used in conjunction with the Inertial Navigation Unit (INU) and Kalman filtering. However, the performance of a shift-based algorithm, when the shifts are derived from the affine transformation, would be much improved compared to current algorithms because the shifts--as well as the other parameters--can be obtained between widely separated images. Thus, the main advantage of this new approach is that, allowing the tracked window to expand and rotate, in addition to moving laterally, enables one to correlate images over a very long time span which, in turn, translates into a large spatial baseline resulting in a proportionately higher depth accuracy.
We describe a model-based vision system to assist pilots in landing maneuvers under restricted visibility conditions. The system was designed to analyze image sequences obtained from a Passive Millimeter Wave (PMMW) imaging system mounted on the aircraft to delineate runways/taxiways, buildings, and other objects on or near runways. PMMW sensors have good response in a foggy atmosphere; but, their spatial resolution is very low. However, additional data such as airport model and approximate position and orientation of aircraft are available. We exploit these data to guide our model-based system to locate objects in the low resolution image and generate warning signals to alert the pilots. We also derive analytical expressions for the accuracy of the camera position estimate obtained by detecting the position of known objects in the image.
One essential parameter used in the estimation of radiative and turbulent heat fluxes from satellite data is surface temperature. Sea and land surface temperature (SST and LST) retrieval algorithms that utilize the thermal infrared portion of the spectrum have been developed, with the degree of success dependent primarily upon the variability of the surface and atmospheric characteristics. However, little effort has been directed to the retrieval of the sea ice surface temperature (IST) in the Arctic and Antarctic pack ice or the ice sheet surface temperature over Antarctica and Greenland. The reason is not one of methodology, but rather our limited knowledge of atmospheric temperature, humidity, and aerosol vertical, spatial and temporal distributions, the microphysical properties of polar clouds, and the spectral characteristics of snow, ice, and water surfaces. Over the open ocean the surface is warm, dark, and relatively homogeneous. This makes SST retrieval, including cloud clearing, a fairly straightforward task. Over the ice, however, the surface within a single satellite pixel is likely to be highly heterogeneous, a mixture of ice of various thicknesses, open water, and snow cover in the case of sea ice. Additionally, the Arctic is cloudy - very cloudy - with typical cloud cover amounts ranging from 60-90 percent. There are few observations of cloud cover amounts over Antarctica. The goal of this research is to increase our knowledge of surface temperature patterns and magnitudes in both polar regions, by examining existing data and improving our ability to use satellite data as a monitoring tool. Four instruments are of interest in this study: the AVHRR, ATSR, SMMR, and SSM/I. Our objectives are as follows. Refine the existing AVHRR retrieval algorithm defined in Key and Haefliger (1992; hereafter KH92) and applied elsewhere. Develop a method for IST retrieval from ATSR data similar to the one used for SST. Further investigate the possibility of estimating surface temperature from passive microwave data (in conjunction with AVHRR clear sky samples) through the use of 'effective emissivities' and physical relationships between skin temperature and subsurface temperature. Use the general method outlined in MK93 to calculate a 12-year record of clear sky equivalent surface temperatures, or possibly all-sky snow-ice interface physical temperatures, from SMMR and SSM/I, compare these temperatures to climatologies, ECMWF modeled surface temperatures, and surface temperatures predicted by a 2-D ice model. And intercompare several ice surface retrieval methods and validate them against ground measurements from the Swiss Camp on the Greenland ice sheet. Additionally, we intend to develop a surface temperature product based on AVHRR data and possibly blended with drifting buoy and meteorological station temperatures.
An adaptive state space architecture is combined with diktiometric representation to provide the framework for designing a robot mapping system with flexible navigation planning tasks. This involves indexing waypoints described as expectations, geometric indexing, and perceptual indexing. Matching and updating the robot's projected position and sensory inputs with indexing waypoints involves matchers, dynamic priorities, transients, and waypoint restructuring. The robot's map learning can be opganized around the principles of passive mapping.
Progress by the Georgia Institute of Technology's Laboratory for Radio-science and Remote Sensing in developing techniques for passive microwave retrieval of water vapor profiles and cloud and precipitation parameters using millimeter and submillimeter wavelength channels is reviewed. Channels of particular interest are in the tropospheric transmission windows at 90, 166, 220, 340, and 410 GHz and centered around the water vapor lines at 183 and 325 GHz. Collectively, these channels have potential application in high-resolution precipitation mapping (e.g., from geosynchronous orbit), remote sensing of cloud and precipitation parameters, including cirrus ice mass, and improved retrieval of water vapor profiles. During the period from January 1, 1994 through June 30, 1994 research activities focussed on calibrating and interpreting data from the Millimeter-Wave Imaging Radiometer (MIR). The MIR was deployed on the NASA ER-2 during the Convective Atmospheric Moisture Experiment (CAMEX, September-October 1993) to obtain the first submillimeter-wave tropospheric imagery of convective precipitations. A 325-GHz radiometer consisted of a submillimeter-wave DSB receiver with three IF channels at +/- 1, 3, and 8.5 GHz, and approximately 14 dB DSB noise figure was successfully operated during these experiments. Activities supported under this grant include a study of the impact of local oscillator reflections from the MIR calibration loads, the development of optimal gain and offset filters for radiometric calibration, and the modeling and interpretation of the MIR 325-GHz data over both clear and cloudy atmospheres. In addition, polarimetric radiometer measurements and modeling for ocean surface and atmospheric cloud-ice studies_were supported.
A passive, millimeter wave imaging sensor for aircraft landing in low or poor visibility conditions is described. The sensor can be incorporated in a camera for future enhanced/synthetic vision systems. Contrast is provided by differences in material reflectivities, temperature, and sky illumination of the scene being imaged. Photographic images of the system's fog penetration capabilities are presented. A combinatorial geometry technique is used to construct the scene geometries. This technique uses eight basic geometric shapes which are used as building blocks for 3-D complex-shaped objects. The building blocks are then combined via union, intersection and exclusion operations to form 3-D scene objects and the combinatorial geometry package determines ray intercepts with scene objects, providing the specific surfaces and propagation distance for the scene.
An apparatus for acquiring signals emitted by a fetus, identifying fetal heart beats and determining a fetal heart rate is presented. Multiple sensor signals are outputted by a passive fetal heart rate monitoring sensor. Multiple parallel nonlinear filters filter these multiple sensor signals to identify fetal heart beats in the signal data. A processor determines a fetal heart rate based on these identified fetal heart beats. The processor includes the use of a figure of merit weighting of heart rate estimates based on the identified heart beats from each filter for each signal. The fetal heart rate thus determined is outputted to a display, storage, or communications channel. A method for enhanced fetal heart beat discrimination includes acquiring signals from a fetus, identifying fetal heart beats from the signals by multiple parallel nonlinear filtering, and determining a fetal heart rate based on the identified fetal heart beats. A figure of merit operation in this method provides for weighting a plurality of fetal heart rate estimates based on the identified fetal heart beats and selecting the highest ranking fetal heart rate estimate.
Investigations designed to study land surface hydrologic-atmospheric interactions, showing the potential of L band passive microwave radiometry for measuring surface soil moisture over large areas, are discussed. Satisfying the data needs of these investigations requires the ability to map large areas rapidly. With aircraft systems this means a need for more beam positions over a wider swath on each flightline. For satellite systems the essential problem is resolution. Both of these needs are currently being addressed through the development and verification of Electronically Scanned Thinned Array Radiometer (ESTAR) technology. The ESTAR L band radiometer was evaluated for soil moisture mapping applications in two studies. The first was conducted over the semiarid rangeland Walnut Gulch watershed located in south eastern Arizona (U.S.). The second was performed in the subhumid Little Washita watershed in south west Oklahoma (U.S.). Both tests showed that the ESTAR is capable of providing soil moisture with the same level of accuracy as existing systems.
During the first half of our second project year we have accomplished the following: (1) acquired a new AVHRR data set for the Beaufort Sea area spanning an entire year; (2) acquired additional ATSR data for the Arctic and Antarctic now totaling over seven months; (3) refined our AVHRR Arctic and Antarctic ice surface temperature (IST) retrieval algorithm, including work specific to Greenland; (4) developed ATSR retrieval algorithms for the Arctic and Antarctic, including work specific to Greenland; (5) investigated the effects of clouds and the atmosphere on passive microwave 'surface' temperature retrieval algorithms; (6) generated surface temperatures for the Beaufort Sea data set, both from AVHRR and SSM/I; and (7) continued work on compositing GAC data for coverage of the entire Arctic and Antarctic. During the second half of the year we will continue along these same lines, and will undertake a detailed validation study of the AVHRR and ATSR retrievals using LEADEX and the Beaufort Sea year-long data. Cloud masking methods used for the AVHRR will be modified for use with the ATSR. Methods of blending in situ and satellite-derived surface temperature data sets will be investigated.
Deployable reflector antennas represent a proven technology with obvious benefits for mobile satellite applications. Harris Corporation has provided deployable reflector antennas for NASA's Tracking and Data Relay Satellite System (TDRSS). These antennas utilize a rigid, radial rib unfurlable reflector with a wire mesh surface. This type of mesh has been identified as a potential design risk for multichannel communications applications based on the potential for generation of Passive Intermodulation (PIM). These concerns are based on the existence of numerous, nonpermanent metal to metal contacts that are inherent to the mesh design. To address this issue, Harris has an ongoing IR&D program to characterize mesh PIM performance. This paper presents the results of the investigation into mesh PIM performance to date and provides background information on the design and performance of the Harris radial rib deployable reflector.
The passive accelerometer system (PAS) is a simple moving ball accelerometer capable of measuring the small magnitude steady relative acceleration that occurs in a low earth orbit spacecraft due to atmospheric drag and the earth's gravity gradient. The accelerometer can be used when the spacecraft continuously rotates during the orbit such that some line of reference in the craft always points along the vector connecting the earth's mass center with the spacecraft mass center. PAS was used successfully on the first United States Microgravity Laboratory (USML-1).
During the second phase project year we have made progress in the development and refinement of surface temperature retrieval algorithms and in product generation. More specifically, we have accomplished the following: (1) acquired a new advanced very high resolution radiometer (AVHRR) data set for the Beaufort Sea area spanning an entire year; (2) acquired additional along-track scanning radiometer(ATSR) data for the Arctic and Antarctic now totalling over eight months; (3) refined our AVHRR Arctic and Antarctic ice surface temperature (IST) retrieval algorithm, including work specific to Greenland; (4) developed ATSR retrieval algorithms for the Arctic and Antarctic, including work specific to Greenland; (5) developed cloud masking procedures for both AVHRR and ATSR; (6) generated a two-week bi-polar global area coverage (GAC) set of composite images from which IST is being estimated; (7) investigated the effects of clouds and the atmosphere on passive microwave 'surface' temperature retrieval algorithms; and (8) generated surface temperatures for the Beaufort Sea data set, both from AVHRR and special sensor microwave imager (SSM/I).
The scientific objectives of this grant are: (1) thoroughly evaluate, both theoretically and empirically, all available Special Sensor Microwave Imager (SSM/I) retrieval algorithms for column water vapor, column liquid water, and surface wind speed; (2) where both appropriate and feasible, develop, validate, and document satellite passive microwave retrieval algorithms that offer significantly improved performance compared with currently available algorithms; and (3) refine and validate a novel physical inversion scheme for retrieving rain rate over the ocean. This report summarizes work accomplished or in progress during the first year of a three year grant. The emphasis during the first year has been on the validation and refinement of the rain rate algorithm published by Petty and on the analysis of independent data sets that can be used to help evaluate the performance of rain rate algorithms over remote areas of the ocean. Two articles in the area of global oceanic precipitation are attached.
The potential for remote sensing of ocean wave direction using passive polarimetric microwave observations was investigated. A fixed-beam 91.65 GHz polarimetric radiometer was mounted on the NASA DC-8 aircraft during the Tropical Ocean Global Atmosphere/Coupled Ocean Atmosphere Response Experiment (TOGA/COARE January - February 1993). Several experiments were performed during which the DC-8 was flown in constant bank-angle turns at approximately 1.5 km altitude to obtain azimuthal scans of the sea surface at fixed observation angles. Data at 65 deg from nadir are consistent with previous findings using 19 and 37 GHz Special Sensor Microwave Imager (SSM/1) satellite observations and support the claim that a broadband emission mechanism is responsible for the azimuthal brightness signatures. Accordingly, a tilted-facet geometrical optics (GO) model of the surface was developed to investigate emission from deterministic and random striated surfaces. Laboratory measurements of polarimetric emission at 92 GHz from small-amplitude water-waves corroborate this model.