Solar Gamma-Ray Spectroscopy

Interactions of ions accelerated in solar flares produce gamma-ray lines and continuum and neutrons. These emissions contain a rich set of observables that provides information about both the accelerated ions and the environment where the ions are transported and interact. Ion interactions with the various nuclei present in the ambient medium produce gamma-ray lines at unique energies. How abundance information is extracted from the measurements is discussed and results from analyses of a number of solar flares are presented. The analyses indicate that the composition of the ambient gas where the ions interact (typically at chromospheric densities) is different from that of the photosphere and more like the composition of the corona, exhibiting low-FIP elemental enhancements that may vary from flare to flare. Evidence for increased Ne/O and the photospheric ³He abundance is also discussed.     

The Local Bubble and Interstellar Material Near the Sun

The properties of interstellar matter at the Sun are regulated by our location with respect to a void in the local matter distribution, known as the Local Bubble. The Local Bubble (LB) is bounded by associations of massive stars and fossil supernovae that have disrupted dense interstellar matter (ISM), driving low density intermediate velocity ISM into the void. The Sun appears to be located in one of these flows of low density material. This nearby interstellar matter, dubbed the Local Fluff, has a bulk velocity of ∼19 km s⁻¹ in the local standard of rest. The flow is coming from the direction of the gas and dust ring formed where the Loop I supernova remnant merges into the LB. Optical polarization data suggest that the local interstellar magnetic field lines are draped over the heliosphere. A longstanding discrepancy between the high thermal pressure of plasma filling the LB and low thermal pressures in the embedded Local Fluff cloudlets is partially mitigated when the ram pressure component parallel to the cloudlet flow direction is included.     

Remote data sensing using SAR and harmonic reradiators

In sensor networks distributed over large areas, communication by means of active transmitters on sensor nodes is inherently energy expensive and poses a significant bottleneck to achieve a long battery life. We propose modulated reradiation of radar illumination as a means to transmit information from a group of sensors to an airborne radar. This puts the communications energy burden on the radar transmitter rather than on the sensor nodes, thus increasing their battery lifetimes. To distinguish the sensor return from the clutter return, the modulation on the sensors is done by switching a nonlinear load on the sensor antenna and processing the harmonic reradiation. We present techniques to transmit information from the sensors, which use stripmap mode synthetic aperture radar (SAR) ideas to decode the information and to simultaneously obtain a geographic map of the sensor locations.     

The Solar Chemical Composition

We present our current knowledge of the solar chemical composition based on the recent significant downward revision of the solar photospheric abundances of the most abundant metals. These new solar abundances result from the use of a 3D hydrodynamic model of the solar atmosphere instead of the classical 1D hydrostatic models, accounting for departures from LTE, and improved atomic and molecular data. With these abundances, the new solar metallicity, Z, decreases to Z=0.012, almost a factor of two lower than earlier widely used values. We compare our values with data from other sources and analyse a number of impacts of these new photospheric abundances. While resolving a number of longstanding problems, the new 3D-based solar photospheric composition also poses serious challenges for the standard solar model as judged by helioseismology.     

Steady-state analysis of the constant-frequency clamped seriesresonant converter

A constant-frequency diode-clamped series resonant converter (CFCSRC) is proposed as a solution to problems associated with frequency-controlled resonant converters. This converter has two resonant frequencies, and control is achieved by varying the relative time spent at each switching frequency. Two zero-current-switching (ZCS) modes are examined and plotted in the output plane. An equation is given for the boundary between the two ZCS modes, as well as an expression for the boundary between ZCS and non-ZCS operation; both are plotted in the output plane. The output equation for the main mode is shown to be hyperbolic. Converter peak voltages limited to the input voltages, and peak currents are less than those of the frequency-controlled clamped series resonant converter over a large operating range. Data from a prototype converter are compared with theoretical data and are shown to be in good agreement with the theoretical model     

Multiple target tracking using products of position measurements

The continued development of the symmetric measurement equation (SME) filter for track maintenance in multiple target tracking (MTT) is considered, focusing on the case in which the SMEs are generated by forming sums of products of the original position measurements. The SME filter is developed for the case of N targets whose motions consist of random perturbations about constant-velocity trajectories. It is assumed that measurements of x-coordinate positions are available, and that the number of measurements is equal to the number of targets. Various analytical properties of the SME filter are studied. It is shown that under a very weak condition, the estimation error equation is locally exponentially stable. The performance of the SME filter is investigated by comparing it with an optimal (minimum-variance) estimator and by generating a computer simulation in the six-target case     

Speech Data Rate Reduction Part II: Applicability of Sensitivity and Error Analysis

This paper deals with the application of modern estimation techniques to the problem of speech data rate reduction. It is desirable to adaptively identify and quantitize the parameters of the speech model. These paramaters cannot be identified and quantized exactly; the performance of the predictor is thereby degraded and this could prevent data reduction. In many cases it is desirable to emply a suboptimal predictor in order to simplify the algorithms, and predictor performance is again degraded. This paper develops sensitivity and error analysis as a potential method for determining quantitatively how speech data reduction system performance is degraded by imprecise parameter knowledge or suboptimal filtering. An intended use of the sensitivity and error analysis algorithms is to determine parameter identification and model structure requirements of configuration concepts for adaptive speech digitizers. First, sensitivity and error analysis algorithms are presented that form the basis for the remainder of the work. The algorithms are then used to determine how imprecise knowledge of vocal tract parameters degrades predictor performance in speech. Transversal filters have previously been proposed for this application. The sensitivity analysis algorithms are then used to determine when and by how much the transverse filter is suboptimal to the Kalman filter. In particular, the question of how effectively a higher order of all-pole model approximates a system with zeros is answered, as this question is of considerable importance in speech. Finally, the physical significance of the innovations process in speech data rate reduction is studied.