High-Energy Electron Beam Relaxation in a Stationary Plasma Thruster

In the paper, processes of high-energy electron beam interaction with plasma particles in a discharge channel of a stationary plasma thruster are analyzed and the results are presented.     

Homologous flare–CME events and their metric type II radio burst association

Active region NOAA 11158 produced many flares during its disk passage. At least two of these flares can be considered as homologous: the C6.6 flare at 06:51 UT and C9.4 flare at 12:41 UT on February 14, 2011. Both flares occurred at the same location (eastern edge of the active region) and have a similar decay of the GOES soft X-ray light curve. The associated coronal mass ejections (CMEs) were slow (334 and 337 km/s) and of similar apparent widths (43° and 44°), but they had different radio signatures. The second event was associated with a metric type II burst while the first one was not. The COR1 coronagraphs on board the STEREO spacecraft clearly show that the second CME propagated into the preceding CME that occurred 50 min before. These observations suggest that CME–CME interaction might be a key process in exciting the type II radio emission by slow CMEs.     

The Spacelab-Mir-1 "Greenhouse-2" experiment.

The Spacelab-Mir-1 (SLM-1) mission is the first docking of the Space Shuttle Atlantis (STS-71) with the Orbital Station Mir in June 1995. The SLM-1 "Greenhouse-2" experiment will utilize the Russian-Bulgarian-developed plant growth unit (Svet). "Greenhouse-2" will include two plantings (1) designed to test the capability of Svet to grow a crop of Superdwarf wheat from seed to seed, and (2) to provide green plant material for post-flight analysis. Protocols, procedures, and equipment for the experiment have been developed by the US-Russian science team. "Greenhouse-2" will also provide the first orbital test of a new Svet Instrumentation System (SIS) developed by Utah State University to provide near real time data on plant environmental parameters and gas-exchange rates. SIS supplements the Svet control and monitoring system with additional sensors for substrate moisture, air temperature, IR leaf temperature, light, oxygen, pressure, humidity, and carbon-dioxide. SIS provides the capability to monitor canopy transpiration and net assimilation of the plants growing in each vegetation unit (root zone) by enclosing the canopy in separate, retractable, ventilated leaf chambers. Six times during the seed-to-seed experiment, plant samples will be collected, leaf area measured, and plant parts fixed and/or dried for ground analysis. A second planting initiated 30 days before the arrival of a U.S. Shuttle [originally planned to be STS-71] is designed to provide green material at the vegetative development stage for ground analysis. [As this paper is being edited, the experiment has been delayed until after the arrival of STS-71.]     

Optimal speckle reduction in polarimetric SAR imagery

Speckle is a major cause of degradation in synthetic aperture radar (SAR) imagery. With the availability of fully polarimetric SAR data, it is possible to use the three complex elements (HH, HV, VV) of the polarimetric scattering matrix to reduce speckle. The optimal method for combining the elements of the scattering matrix to minimize image speckle is derived, and the solution is shown to be a polarimetric whitening filter (PWF). A simulation of spatially correlated, K-distributed, fully polarimetric clutter is then used to compare the PWF with other, suboptimal speckle-reduction methods. Target detection performance of the PWF, span, and single-channel |HH|² detectors is compared with that of the optimal polarimetric detector (OPD). A novel, constant-false-alarm-rate (CFAR) detector (the adaptive PWF) is as a simple alternative to the OPD for detecting targets in clutter. This algorithm estimates the polarization covariance of the clutter, uses the covariance to construct the minimum-speckle image, and then tests for the presence of a target. An exact theoretical analysis of the adaptive PWF is presented; the algorithm is shown to have detection performance comparable with that of the OPD     

Single-phase power distribution system power flow and faultanalysis

Alternative methods for power flow and fault analysis of single-phase distribution systems are presented. The algorithms for both power flow and fault analysis utilize a generalized approach to network modeling. The generalized admittance matrix, formed using elements of linear graph theory, is an accurate network model for all possible single-phase network configurations. Unlike the standard nodal admittance matrix formulation algorithms, the generalized approach uses generalized component models for the transmission line and transformer. The standard assumption of a common node voltage reference point is not required to construct the generalized admittance matrix. Therefore, truly accurate simulation results can be obtained for networks that cannot be modeled using traditional techniques     

Landsat satellite imagery of the Qattara Depression area,Egypt

The Qattara Depression lies in the northern part of the Western Desert of Egypt at a distance of some tens of kilometers to the south of the Mediterranean Sea Coast. The depression in question is the largest one in the great Sahara extending across North Africa. It covers an area of some 19,000 km² at ? 60 m level and the absolute level of its lowest point is about ? 134 m. The depression extends for about 300 km in a roughly ENE-WSW direction, while its width is variable reaching to a maximum of about 145 km. Feasibility studies are currently carried out for the Qattara solar-hydro-electric project which aims at generating hydro-electric power by the drop of the Mediterranean Sea water into the depression after passing through a canal/tunnel system. Peak load electric power may be also generated by raising the water to the small hollow of Deir Kirayim, situated at a higher level near the depression, and allowing it to drop to a low level.For the purpose of assessing the regional criteria involved in the implementation of the project and the environmental impact of such implementation, the Qattara Depression and the surrounding area has been studied on a regional scale by the utilization of LANDSAT satellite imagery. The maps produced by the interpretation of the images in question include those of the geological and environmental units, structural lineations, drainage and vegetation cover. Lineation density and drainage density maps are derived by the computation of the structural lineation and drainage maps respectively. A map of groundwater conditions is worked out on the basis of the image interpretation, and the observations previously carried out on the groundwater aquifers in the Qattara Depression and the surrounding area. LANDSAT satellite image interpretation and computation are supported by intensive observations carried out in the field as well as chemical, petrological and mineralogical analyses of the samples collected.The LANDSAT satellite images proved to be of great importance in mapping the Qattara Depression floor which is hardly accessible to classical mapping, and especially in view of the large area which could be covered by imagery mapping in a reasonably short time compatible with the duration of the feasibility study. The special characters of the spaceborne multispectral imagery have been paramount in deciphering the major regional features of the investigated area.The overall synoptic picture of the regional setting of the geological and environmental units, faults, fractures and folds, drainage lines and plant cover in the large area studied has been clarified for the first time. It has been demonstrated that the Qattara Depression is actually constituted of several small depressions. The environmental impact of the project implementation has been visualized especially regarding the possible influence of the saline water on the fresh groundwater sources. The thick salt accumulation in the depression has been found to be of such extension as to increase the salinity of the Mediterranean Sea water stored in the depression following the implementation of the project. The lineation density map has been particularly of great help in the localization of sites subjected to intense crustal deformation, greater slope instability and run off surface water flooding.     

Data fusion of decentralized local tracker outputs

An approach for fusing offboard track-level data at a central fusion node is presented. The case where the offboard tracker continues to update its local track estimate with measurement and system dynamics models that are not necessarily linear is considered. An algorithm is developed to perform this fusion at a central node without having access to the offboard measurements, their noise statistics, or the location of the local estimator. The algorithm is based on an extension of results that were originally established for linear offboard trackers. A second goal of this work is to develop an inequality constraint for selecting the proper sampling interval for the incoming state estimates to the fusion node. This interval is selected to allow use of conventional Kalman filter algorithms at the fusion node without suffering error performance degradation due to processing a correlated sequence of track state estimates     

Exploiting GNSS signal structure to enhance observability

There are a number of different error sources, such as multipath and thermal noise, which corrupt satellite navigation waveforms from their theoretical structure. However, even under ideal conditions the broadcast signals have some degree of deformation as a result of the practical individual hardware implementation. For the most demanding users of satellite navigation, such as aircraft navigation and landing systems, it is important to characterize the nominal signal structure in order to detect minimal variations resulting from hardware-based errors. Thus far such precorrelation Global Navigation Satellite System (GNSS) signal quality monitoring has been performed through high gain antennas, which allow for raising the GNSS spectrum above the thermal noise floor and observing the structure of the signal directly at the front end output. This paper describes a new approach to achieve such observability based on signal processing techniques, such as dithering and averaging, which leverage the repetitive nature of the GNSS signal. The paper presents how these techniques can drastically improve the signal-to-noise ratio (SNR) in postprocessing, allowing for the direct analysis of GNSS signals using traditional front end designs and conventional antennas. Results are predicted using the appropriate theory and validated using data collected from the Global Positioning System (GPS).