Polar magnetic disturbances and field-aligned currents

The results of research of the morphology and physics of polar magnetic disturbances and their connection with three-dimensional magnetospheric currents are reviewed. Magnetic disturbance current systems are examined, also their relation to solar wind parameters and magnetic activity level and their seasonal dependence. On the basis of numerical model calculations it is shown that magnetospheric field-aligned currents observed by the TRIAD and ISIS-2 satellites are the main generation mechanism of high-latitude magnetic disturbances. Plasma pressure gradients are examined as a source of energy for driving field-aligned currents in the closed magnetosphere.     

Detection in correlated Gaussian plus impulsive noise

A detector which is designed to operate in a correlated Gaussian-plus-impulsive-noise environment is presented. The detector whitens the data robustly and then uses a two-sided threshold test to determine the presence of impulsive samples. The impulsive samples are discarded, and the remaining samples are used to detect the presence or absence of a signal using a matched filter. An approximate analysis is presented, and simulations are used to demonstrate the effectiveness of this approach     

Doppler imaging based on radar target precession

A unique form of target motion reminiscent of the precession of a rotating top is investigated. Images are generated with the radar looking either along the precession axis or orthogonally to it. Features of the two methods are discussed and demonstrated by imaging simulated point target scenes     

A Gaussian Mixture PHD Filter for Jump Markov System Models

The probability hypothesis density (PHD) filter is an attractive approach to tracking an unknown and time-varying number of targets in the presence of data association uncertainty, clutter, noise, and detection uncertainty. The PHD filter admits a closed-form solution for a linear Gaussian multi-target model. However, this model is not general enough to accommodate maneuvering targets that switch between several models. In this paper, we generalize the notion of linear jump Markov systems to the multiple target case to accommodate births, deaths, and switching dynamics. We then derive a closed-form solution to the PHD recursion for the proposed linear Gaussian jump Markov multi-target model. Based on this an efficient method for tracking multiple maneuvering targets that switch between a set of linear Gaussian models is developed. An analytic implementation of the PHD filter using statistical linear regression technique is also proposed for targets that switch between a set of nonlinear models. We demonstrate through simulations that the proposed PHD filters are effective in tracking multiple maneuvering targets.     

A method for representing the thermodynamic and thermophysical functions in simulation of powerplant processes

A method for representing thermodynamic and thermophysical functions is presented; the functions make it possible to simulate thermal and gasodynamic processes in powerplants that use different individual substances or their mixtures as a working fluid. The method also involves consideration of real gas properties.     

A Twin-CME Scenario for Ground Level Enhancement Events

Ground Level Enhancement (GLEs) events are extreme Solar Energetic Particle (SEP) events. Protons in these events often reach ～GeV/nucleon. Understanding the underlying particle acceleration mechanism in these events is a major goal for Space Weather studies. In Solar Cycle 23, a total of 16 GLEs have been identified. Most of them have preceding CMEs and in-situ energetic particle observations show some of them are enhanced in ICME or flare-like material. Motivated by this observation, we discuss here a scenario in which two CMEs erupt in sequence during a short period of time from the same Active Region (AR) with a pseudo-streamer-like pre-eruption magnetic field configuration. The first CME is narrower and slower and the second CME is wider and faster. We show that the magnetic field configuration in our proposed scenario can lead to magnetic reconnection between the open and closed field lines that drape and enclose the first CME and its driven shock. The combined effect of the presence of the first shock and the existence of the open close reconnection is that when the second CME erupts and drives a second shock, one finds both an excess of seed population and an enhanced turbulence level at the front of the second shock than the case of a single CME-driven shock. Therefore, a more efficient particle acceleration will occur. The implications of our proposed scenario are discussed.     

Ceramic ChemCam Calibration Targets on Mars Science Laboratory

The ChemCam instrument on the Mars Science Laboratory rover Curiosity will use laser-induced breakdown spectroscopy (LIBS) to analyze major and minor element chemistry from sub-millimeter spot sizes, at ranges of ～1.5–7?m. To interpret the emission spectra obtained, ten calibration standards will be carried on the rover deck. Graphite, Ti?metal, and four glasses of igneous composition provide primary, homogeneous calibration targets for the laser. Four granular ceramic targets have been added to provide compositions closer to soils and sedimentary materials like those expected at the Gale Crater field site on Mars. Components used in making these ceramics include basalt, evaporite, and phyllosilicate materials that approximate the chemical compositions of detrital and authigenic constituents of clastic and evaporite sediments, including the elevated sulfate contents present in many Mars sediments and soils. Powdered components were sintered at low temperature (800?°C) with a small amount (9?wt.%) of lithium tetraborate flux to produce ceramics that retain volatile sulfur yet are durable enough for the mission. The ceramic targets are more heterogeneous than the pure element and homogenous glass standards but they provide standards with compositions more similar to the sedimentary rocks that will be Curiosity’s prime targets at Gale Crater.     

Late Stages of Stellar Evolution

A large fraction of ISO observing time was used to study the late stages of stellar evolution. Many molecular and solid state features, including crystalline silicates and the rotational lines of water vapour, were detected for the first time in the spectra of (post-)Asymptotic Giant Branch (AGB) stars. Their analysis has greatly improved our knowledge of stellar atmospheres and circumstellar environments. A surprising number of objects, particularly young planetary nebulae with Wolf-Rayet (WR) central stars, were found to exhibit emission features in their ISO spectra that are characteristic of both oxygen-rich and carbon-rich dust species, while far-IR observations of the PDR around NGC 7027 led to the first detections of the rotational line spectra of CH and CH⁺. Based on observations with ISO, an ESA project with instruments funded by ESA Member States (especially the PI countries: France, Germany, The Netherlands, and the United Kingdom), and with the participation of ISAS and NASA.     

Online INS/GPS integration with a radial basis function neural network

Most of the present navigation systems rely on Kalman filtering to fuse data from global positioning system (GPS) and the inertial navigation system (INS). In general, INS/GPS integration provides reliable navigation solutions by overcoming each of their shortcomings, including signal blockage for GPS and growth of position errors with time for INS. Present Kalman filtering INS/GPS integration techniques have some inadequacies related to the stochastic error models of inertial sensors, immunity to noise, and observability. This paper aims to introduce a multi-sensor system integration approach for fusing data from INS and GPS utilizing artificial neural networks (ANN). A multi-layer perceptron ANN has been recently suggested to fuse data from INS and differential GPS (DGPS). Although being able to improve the positioning accuracy, the complexity associated with both the architecture of multi-layer perceptron networks and its online training algorithms limit the real-time capabilities of this technique. This article, therefore, suggests the use of an alternative ANN architecture. This architecture is based on radial basis function (RBF) neural networks, which generally have simpler architecture and faster training procedures than multi-layer perceptron networks. The INS and GPS data are first processed using wavelet multi-resolution analysis (WRMA) before being applied to the RBF network. The WMRA is used to compare the INS and GPS position outputs at different resolution levels. The RBF-ANN module is then trained to predict the INS position errors and provide accurate positioning of the moving platform. Field-test results have demonstrated that substantial improvement in INS/GPS positioning accuracy could be obtained by applying the combined WRMA and RBF-ANN modules.