Langmuir Turbulence and Solar Radio Bursts

Langmuir waves and turbulence resulting from an electron beam-plasma instability play a fundamental role in the generation of solar radio bursts. We report recent theoretical advances in nonlinear dynamics of Langmuir waves. First, starting from the generalized Zakharov equations, we study the parametric excitation of solar radio bursts at the fundamental plasma frequency driven by a pair of oppositely propagating Langmuir waves with different wave amplitudes. Next, we briefly discuss the emergence of chaos in the Zakharov equations. We point out that chaos can lead to turbulence in the source regions of solar radio emissions. This revised version was published online in August 2006 with corrections to the Cover Date.     

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.     

Radial and meridional trends in solar wind thermal electron temperature and anisotropy: Ulysses

Ulysses plasma measurement from 1.15 to 5.31 AU and from S6.4° to S48.3° solar latitude are used to assess the trends in the solar wind thermal electron temperature and anisotropy. Improved spacecraft potential corrections and data products have been incorporated. The radial temperature gradient is steeper than in previous determinations, but flatter than adiabatic. When normalized to 1 AU, temperature decrease with increasing latitude. Little change in the average thermal anisotropy has been seen during the mission.     

Solar wind corotating stream interaction regions out of the ecliptic plane: Ulysses

Ulysses plasma observations reveal that the forward shocks that commonly bound the leading edges of corotating interaction regions (CIRs) beyond 2 AU from the Sun at low heliographic latitudes nearly disappeared at a latitude of S26°. On the other hand, the reverse shocks that commonly bound the trailing edges of the CIRs were observed regularly up to S41.5°, but became weaker with increasing latitude. Only three CIR shocks have been observed poleward of S41.5°; all of these were weak reverse shocks. The above effects are a result of the forward waves propagating to lower heliographic latitudes and the reverse waves to higher latitudes with increasing heliocentric distance. These observational results are in excellent agreement with the predictions of a global model of solar wind flows that originate in a simple tilted-dipole geometry back at the Sun.     

Multistage integration model for human egomotion perception

Human computational vision models that attempt to account for the dynamic perception of egomotion and relative depth typically assume a common three-stage process: first, compute the optical flow field based on the dynamically changing image; second, estimate the egomotion states based on the flow; and third, estimate the relative depth/shape based on the egomotion states and possibly on a model of the viewed surface. We propose a model more in line with recent work in human vision, employing multistage integration. Here the dynamic image is first processed to generate spatial and temporal image gradients that drive a mutually interconnected state estimator and depth/shape estimator. The state estimator uses the image gradient information in combination with a depth/shape estimate of the viewed surface and an assumed model of the viewer's dynamics to generate current state estimates; in tandem, the depth/shape estimator uses the image gradient information in combination with the viewer's state estimate and assumed shape model to generate current depth/shape estimates. In this paper, we describe the model and compare model predictions with empirical data.     

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     

Design of a Correlator for Real-Time Video Comparisons

The problem of locating a reference image within a larger image using a correlation technique is discussed. Although the particular application discussed is that of locating a reference image obtained from one video sensor or a photograph, within the larger field of view obtained from a second video sensor in real time (i.e., at the TV field rate), the results are general and useful for a number of applications. The tradeoffs necessary to obtain real time correlat are discussed and their effect on correlation accuracy is given.     

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.