The multifuid solar wind termination shock and its influence on the threedimensional plasma structure upstream and downstream

The solar wind termination shock is described as a multi-fluid phenomenon taking into account the magnetohydrodynamic self-interaction of a multispecies plasma consisting of solar wind ions, pick-up ions and shock-generated anomalous cosmic ray particles. The spatial diffusion of these high energy particles relative to the resulting, pressure-modified solar wind flow structure is described by a coupled system of differential equations describing mass-, momentum-, and energy-flow continuities for all plasma components. The energy loss due to escape of energetic particles (MeV) from the precursor into the inner heliosphere is taken into account. We determine the integrated properties of the anomalous cosmic ray gas and the low-energy solar wind. Also the variation of the compression ratio of the shock structure is quantitatively determined and is related to the pick-up ion energization efficiency and to the mean energy of the downstream anomalous cosmic ray particles. The variation of the resulting shock structure and of the solar wind sheath plasma extent beyond the shock is discussed with respect to its consequences for the LISM neutral gas filtration and the threedimensional shape of the heliosphere.     

Some active galactic nuclei as cosmological probes

A method of using AGNs as cosmological probes and some recent results are discussed. The method is based on fitting the Hedgehog model to observations of spectra, structure and polarization of AGN radio emission and time variations of the observed quantities. If red shifts of selected AGNs are known, extragalactic distances, the Hubble constant and the deceleration parameter of the Universe can be measured using only radio observations. Recent results may give new strong arguments for the basic model to be in agreement with observations of variable spectra and structure of many AGNs, and may allow preliminary selection of AGNs for further use.     

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.     

The Plasma Environment of Comet 67P/Churyumov-Gerasimenko Throughout the Rosetta Main Mission

The plasma environment of comet 67P/Churyumov-Gerasimenko, the Rosetta mission target comet, is explored over a range of heliocentric distances throughout the mission: 3.25 AU (Rosetta instruments on), 2.7 AU (Lander down), 2.0 AU, and 1.3 AU (perihelion). Because of the large range of gas production rates, we have used both a fluid-based magnetohydrodynamic (MHD) model as well as a semi-kinetic hybrid particle model to study the plasma distribution. We describe the variation in plasma environs over the mission as well as the differences between the two modeling approaches under different conditions. In addition, we present results from a field aligned, two-stream transport electron model of the suprathermal electron flux when the comet is near perihelion.     

Phased array of large reflectors for deep-space communication

In this paper the problem of uplink array calibration for deep-space communication is considered. A phased array of many modest-size reflectors antennas is used to drastically improve the uplink effective isotropic radiated power of a ground station. A radar calibration procedure for the array phase distribution is presented using a number of in-orbit targets. Design of optimal orbit and the number of calibration targets is investigated for providing frequent calibration opportunities needed for compensating array elements phase center movements as the array tracks a spacecraft. Array far-field focusing based on the near-filed in-orbit (low Earth orbit (LEO)) calibration targets is also presented and array gain degradation analysis based on the position error of the array elements and in-orbit targets has been carried out. It is shown that errors in the in-orbit targets positions significantly degrade the far-field array gain while the errors in array elements positions are not very important. Analysis of phase errors caused by thermal noise, system instability, and atmospheric effects show insignificant array gain degradation by these factors     

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.     

What do Cosmogenic Isotopes Tell us About Past Solar Forcing of Climate?

In paleoclimate studies, cosmogenic isotopes are frequently used as proxy indicators of past variations in solar irradiance on centennial and millennial timescales. These isotopes are spallation products of galactic cosmic rays (GCRs) impacting Earth's atmosphere, which are deposited and stored in terrestrial reservoirs such as ice sheets, ocean sediments and tree trunks. On timescales shorter than the variations in the geomagnetic field, they are modulated by the heliosphere and thus they are, strictly speaking, an index of heliospheric variability rather than one of solar variability. Strong evidence of climate variations associated with the production (as opposed to the deposition) of these isotopes is emerging. This raises a vital question: do cosmic rays have a direct influence on climate or are they a good proxy indicator for another factor that does (such as the total or spectral solar irradiance)? The former possibility raises further questions about the possible growth of air ions generated by cosmic rays into cloud condensation nuclei and/or the modulation of the global thunderstorm electric circuit. The latter possibility requires new understanding about the required relationship between the heliospheric magnetic fields that scatter cosmic rays and the photospheric magnetic fields which modulate solar irradiance.     

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