EUV spectroscopy as a plasma diagnostic

The EUV wavelength regions is rich in emission lines from the transition region and the corona. Spectroscopic techniques have been used extensively to determine the physical conditions in the solar atmosphere for such diverse phenomena as coronal holes, active regions, sunspots, flares, etc. The diagnostics and dynamics of plasmas, both homogeneous and inhomogeneous plasmas, are reviewed. The future projects such as the CDS and SUMER instruments on SOHO have been discussed as they cover EUV wavelength region and will provide a wealth of observational data with excellent spatial, spectral, and temporal resolution.     

Blind adaptive decision fusion for distributed detection

We consider the problem of decision fusion in a distributed detection system. In this system, each detector makes a binary decision based on its own observation, and then communicates its binary decision to a fusion center. The objective of the fusion center is to optimally fuse the local decisions in order to minimize the final error probability. To implement such an optimal fusion center, the performance parameters of each detector (i.e., its probabilities of false alarm and missed detection) as well as the a priori probabilities of the hypotheses must be known. However, in practical applications these statistics may be unknown or may vary with time. We develop a recursive algorithm that approximates these unknown values on-line. We then use these approximations to adapt the fusion center. Our algorithm is based on an explicit analytic relation between the unknown probabilities and the joint probabilities of the local decisions. Under the assumption that the local observations are conditionally independent, the estimates given by our algorithm are shown to be asymptotically unbiased and converge to their true values at the rate of O(1/k/sup 1/2/) in the rms error sense, where k is the number of iterations. Simulation results indicate that our algorithm is substantially more reliable than two existing (asymptotically biased) algorithms, and performs at least as well as those algorithms when they work.     

Optimal motion planning for dual-spacecraft interferometry

We address the question of design and optimal control of a class of dual-spacecraft interferometric imaging formations. The first main contribution is that we combine two ideas introduced separately in the literature and propose a maneuver that offers improved imaging performance. We then formulate an optimal control problem to minimize fuel consumption and maximize image quality by minimizing the relative speed, which is proportional to the signal-to-noise ratio (SNR) of the reconstructed image. We show that the necessary conditions are also sufficient and that the resulting optimal control is unique. Finally, we apply a continuation method to solve for the unique optimal trajectory.     

The Pre-CME Sun

The coronal mass ejection (CME) phenomenon occurs in closed magnetic field regions on the Sun such as active regions, filament regions, transequatorial interconnection regions, and complexes involving a combination of these. This chapter describes the current knowledge on these closed field structures and how they lead to CMEs. After describing the specific magnetic structures observed in the CME source region, we compare the substructures of CMEs to what is observed before eruption. Evolution of the closed magnetic structures in response to various photospheric motions over different time scales (convection, differential rotation, meridional circulation) somehow leads to the eruption. We describe this pre-eruption evolution and attempt to link them to the observed features of CMEs. Small-scale energetic signatures in the form of electron acceleration (signified by nonthermal radio bursts at metric wavelengths) and plasma heating (observed as compact soft X-ray brightening) may be indicative of impending CMEs. We survey these pre-eruptive energy releases using observations taken before and during the eruption of several CMEs. Finally, we discuss how the observations can be converted into useful inputs to numerical models that can describe the CME initiation.     

Detection of small objects in clutter using a GA-RBF neural network

Detection of small objects in a radar or satellite image is an important problem with many applications. Due to a recent discovery that sea clutter, the electromagnetic wave backscatter from a sea surface, is chaotic rather than purely random, computational intelligence techniques such as neural networks have been applied to reconstruct the chaotic dynamic of sea clutter. The reconstructed sea clutter dynamical system which usually takes the form of a nonlinear predictor does not only provide a model of the sea scattering phenomenon, but it can also be used to detect the existence of small targets such as fishing boats and small fragments of icebergs by observing abrupt changes in the prediction error. We applied a genetic algorithm (GA) to obtain an optimal reconstruction of sea clutter dynamic based on a radial basis function (RBF) neural network. This GA-RBF uses a hybrid approach that employes a GA to search for the optimum values of the following RBF parameters: centers, variance, and number of hidden nodes, and uses the least square method to determine the weights. It is shown here that if the functional form of an unknown nonlinear dynamical system can be represented exactly using an RBF net (i.e., no approximation error), this GA-RBF approach can reconstruct the exact dynamic from its time series measurements. In addition to the improved accuracy in modeling sea clutter dynamic, the GA-RBF is also shown to enhance the detectability of small objects embedded in the sea. Using real-life radar data that are collected in the east coast of Canada by two different radar systems: a ground-based radar and a satellite equipped with synthetic aperture radar (SAR), we show that the GA-RBF network is a reliable detector for small surface targets in various sea conditions and is practical for real-life search and rescue, navigation, and surveillance applications     

The characteristics of sharp (small-scale) boundaries of solar wind plasma and magnetic field structures

We investigate properties of large (>20%) and sharp (<10 min) solar wind ion flux changes using INTERBALL-1 and WIND plasma and magnetic field measurements from 1996 to 1999. These ion flux changes are the boundaries of small-scale and middle-scale solar wind structures. We describe the behavior of the solar wind velocity, temperature and interplanetary magnetic field (IMF) during these sudden flux changes. Many of the largest ion flux changes occur during periods when the solar wind velocity is nearly constant, so these are mainly plasma density changes. The IMF magnitude and direction changes at these events can be either large or small. For about 55% of the ion flux changes, the sum of the thermal and magnetic pressure are in balance across the boundary. In many of the other cases, the thermal pressure change is significantly more than the magnetic pressure change. We also attempted to classify the types of discontinuities observed.     

A Far Infrared Photometer (FIRP) for the Infrared Telescope in Space (IRTS)

We describe the design and calibration of the Far-Infrared Photometer (FIRP), one of four focal plane instruments on the Infrared Telescope in Space (IRTS). The FIRP will provide absolute photometry in four bands centered at 150, 250, 400, and 700 μm with spectral resolution λ/Δλ ≈ 3 and spatial resolution ΔΘ = 0.5 degrees. High sensitivity is achieved by using bolometric detectors operated at 300 mK in an AC bridge circuit. The closed-cycle ³He refrigerator can be recycled in orbit. A 2 K shutter provides a zero reference for each field of view. More than 10% of the sky will be surveyed during the ≈3 week mission lifetime with a sensitivity of <10⁻¹³ W·cm⁻²·sr⁻¹ per 0.5 degree pixel.     

Spectra and time variability of black-hole binaries in the low/hard state

We propose a jet model for the low/hard state of galactic black-hole X-ray sources which explains the energy spectra from radio to X-rays and a number of timing properties in the X-ray domain such as the time lag spectra, the hardening of the power density spectra and the narrowing of the autocorrelation function with increasing photon energy. The model assumes that (i) there is a magnetic field along the axis of the jet, (ii) the electron density in the jet drops inversely proportional to distance, (iii) the jet is “hotter” near its center than at its periphery, and (iv) the electrons in the jet follow a power-law distribution function. We have performed Monte Carlo simulations of Compton upscattering of soft photons from the accretion disk and have found power-law high-energy spectra with photon-number index in the range 1.5–2 and cutoff at a few hundred keV, power-law time lags versus Fourier frequency with index 0.8, and an increase of the rms amplitude of variability and a narrowing of the autocorrelation function with increasing photon energy as they have been observed in Cygnus X-1. The spectrum at long wavelengths (radio, infrared, optical) is modeled to come from synchrotron radiation of the energetic electrons in the jet. We find flat to inverted radio spectra that extend from the radio up to about the optical band. For magnetic field strengths of the order 10⁵–10⁶ G at the base of the jet, the calculated spectra agree well in slope and flux with the observations.