Proton phase space densities (0.5eV<Ep<5MeV) at midlatitudes from Ulysses SWICS/HI-SCALE measurements

Proton phase space densities in the solar wind frame from suprathermal velocities 10 km s^–1 to 30,000 km s^–1 (0.5 eV–5 MeV) were derived from combined SWICS and HISCALE measurements when Ulysses was at 5 AU and –24° heliolatitude. The period (19–23 January 1993) encompasses a forward/reverse shock pair (20 January, 0500 UT and 22 January, 0300 UT). Strong evidence is found for shock acceleration of pickup protons from interstellar hydrogen at all energies measured.     

Solar wind charge states measured by ULYSSES/SWICS in the south polar hole

The Ulysses mission now has an extensive data base covering several passes of the south polar coronal hole as the spacecraft proceeds to higher latitudes. Using composition measurements from the SWICS experiment on the Ulysses spacecraft, we have obtained charge state distributions, and hence inferred coronal ionization temperatures, for several solar wind species. In particular, we present an overview of Oxygen ionization temperature measurements, based on the O⁷⁺/O⁶⁺ ratio, for the period January 1993 until April 1994 (23°S to 61°S heliographic latitude), and detailed Oxygen, Silicon and Iron charge state distributions of the south polar hole during a two month period of nearly continuous hole coverage, Dec 1993–Jan 1994 (45°S to 52°S heliographic latitude).     

Dignet: an unsupervised-learning clustering algorithm forclustering and data fusion

Dignet is a self-organizing artificial neural network (ANN) that exhibits deterministically reliable behavior-to-noise interference, when the noise does not exceed a prespecified level of tolerance. The complexity of the proposed ANN, in terms of neuron requirements versus stored patterns, increases linearly with the number of stored patterns and their dimensionality. The self-organization of Dignet is based on the idea of competitive generation and elimination of attraction well in the pattern space. Dignet is used for detection and distributed decision fusion. Analytical and numerical results are included     

Multimodule parallel series-loaded resonant converters

The design and implementation of a multimodule parallel series-loaded resonant (SLR) converter system is presented. The SLR converter to be paralleled is operated in the n=2 discontinuous mode (DCM). Its dc analysis and dynamic modeling are made. In parallel operation, an average control technique is proposed to compensate the mismatch in current control characteristics of each parallel converter. Good dynamic and static current sharing characteristics are obtained. In addition, to obtain good output voltage regulating control performance, a design procedure is presented to find the parameters of feedback voltage controller according to the prescribed specifications     

THE CLUSTER ION SPECTROMETRY (CIS) EXPERIMENT

The Cluster Ion Spectrometry (CIS) experiment is a comprehensive ionic plasma spectrometry package on-board the four Cluster spacecraft capable of obtaining full three-dimensional ion distributions with good time resolution (one spacecraft spin) with mass per charge composition determination. The requirements to cover the scientific objectives cannot be met with a single instrument. The CIS package therefore consists of two different instruments, a Hot Ion Analyser (HIA) and a time-of-flight ion COmposition and DIstribution Function analyser (CODIF), plus a sophisticated dual-processor-based instrument-control and Data-Processing System (DPS), which permits extensive on-board data-processing. Both analysers use symmetric optics resulting in continuous, uniform, and well-characterised phase space coverage. CODIF measures the distributions of the major ions (H⁺, He⁺, He⁺⁺, and O⁺) with energies from ~0 to 40 keV/e with medium (22.5°) angular resolution and two different sensitivities. HIA does not offer mass resolution but, also having two different sensitivities, increases the dynamic range, and has an angular resolution capability (5.6° × 5.6°) adequate for ion-beam and solar-wind measurements.     

Detection and range/Doppler estimation for colocated sensors

The problem of multisensor detection and high resolution signal state estimation using joint maximum a posteriori detection and high order nonlinear filtering techniques is addressed. The model-based fusion approach offers the potential for increased target resolution in range/Doppler/azimuth space. The approach employs joint detection/estimation filters (JDEF) for target detection and localization. The JDEF approach segments the aggregate nonlinear model over the entire target resolution space into a number of localized nonlinear models by partitioning the resolution space into a number of resolution subcells. This partitioning leads to extremely accurate state estimation. The proposed JDEF approach has a built-in capability for automatic data alignment from multiple sensors, and can be used for centralized, decentralized, and distributed data fusion.     

Simulation considers the human factors

Human factors aspects of flight simulation design at McDonnell Douglas are considered. Modeling approaches are examined and testing with pilots and cockpits is described.     

Observing the Sun at 20–650 MHz at Thermopylae with Artemis

Fine structure of type IV radio solar bursts with a great variety and complexity often give much information in different ways and enable estimation of various coronal characteristics. In this work, we expose our new method for fine structure revealing and separation of two basic kinds of type IV fine structure, as fibers and pulsations. We also estimate frequency drift of fibers from dynamic spectra, clean from continuous background, with a prototype method using 2-D Fourier transform and we estimate periodicities of fibers as well as pulsations with continuous wavelet transform. Working with the last method we found periodicities close to 3 min umbral oscillations and 5 min global solar oscillations.     

Risk-based technology portfolio optimization for early space mission design

The successful design, development, and operation of space missions requires informed decisions to be made across a vast array of investment, scientific, technological, and operational issues. In the work reported in this paper, we address the problem of determining optimal technology investment portfolios that minimize mission risk and maximize the expected science return of the mission. We model several relationships that explicitly link investment in technologies to mission risk and expected science return. To represent and compute these causal and computational dependencies, we introduce a generalization of influence diagrams that we call inference nets. To illustrate the approach, we present results from its application to a technology portfolio investment trade study done for a specific scenario for the projected 2009 Mars MSL mission. This case study examines the impact of investments in precision landing and long-range roving technologies on the mission capability, and the associated risk, of visiting a set of preselected science sites. We show how an optimal investment strategy can be found that minimizes the mission risk given a fixed total technology investment budget, or alternatively how to determine the minimum budget required to achieve a given acceptable mission risk.