Cosmic Ray Transport in a Heliospheric Magnetic Field with Non-Polar Coronal Holes

The simple tilted dipole picture of Corotating Interaction Regions which prevailed during the first polar pass of Ulysses no longer applies since the Sun entered a more active phase. Recent observations show that CIRs still persist, though the large polar coronal holes of solar minimum shrink to smaller areas and move to lower latitudes. We present 3-D simulations for the cosmic-ray intensity variations in a model with non-polar high speed streams. Latitudinal and recurrent time-variations are discussed, but more detailed and realistic simulations are required before quantitative comparisons with observations can be made. This revised version was published online in August 2006 with corrections to the Cover Date.     

The importance of anisotropic interstellar turbulence and molecular-cloud magnetic mirrors for galactic cosmic-ray propagation

Recent studies suggest that when magnetohydrodynamic (MHD) turbulence is excited by stirring a plasma at large scales, the cascade of energy from large to small scales is anisotropic, in the sense that small-scale fluctuations satisfy the inequality k k , where k and k are, respectively, the components of a fluctuations wave vector and to the background magnetic field. Such anisotropic fluctuations are very inefficient at scattering cosmic rays. Results based on the quasilinear approximation for scattering of cosmic rays by anisotropic MHD turbulence are presented and explained. The important role played by molecular-cloud magnetic mirrors in confining and isotropizing cosmic rays when scattering is weak is also discussed.     

SAR ATR performance using a conditionally Gaussian model

A family of conditionally Gaussian signal models for synthetic aperture radar (SAR) imagery is presented, extending a related class of models developed for high resolution radar range profiles. This signal model is robust with respect to the variations of the complex-valued radar signals due to the coherent combination of returns from scatterers as those scatterers move through relative distances on the order of a wavelength of the transmitted signal (target speckle). The target type and the relative orientations of the sensor, target, and ground plane parameterize the conditionally Gaussian model. Based upon this model, algorithms to jointly estimate both the target type and pose are developed. Performance results for both target pose estimation and target recognition are presented for publicly released data from the MSTAR program     

Observer-type Kalman innovation filter for uncertain linear systems

An observer-type of Kalman innovation filtering algorithm to find a practically implementable "best" Kalman filter, and such an algorithm based on the evolutionary programming (EP) optima-search technique, are proposed, for linear discrete-time systems with time-invariant unknown-but-hounded plant and noise uncertainties. The worst-case parameter set from the stochastic uncertain system represented by the interval form with respect to the implemented "best" filter is also found in this work for demonstrating the effectiveness of the proposed filtering scheme. The new EP-based algorithm utilizes the global optima-searching capability of EP to find the optimal Kalman filter and state estimates at every iteration, which include both the best possible worst case Interval and the optimal nominal trajectory of the Kalman filtering estimates of the system state vectors. Simulation results are included to show that the new algorithm yields more accurate estimates and is less conservative as compared with other related robust filtering schemes     

Particle orbits near a neutral point

We study particle trajectories at an X-type neutral point, in the presence of a time-varying electric field. We present consequent distributions of electrons and protons, and suggest that a disturbance propagating through a neutral point may damp by particle acceleration.     

Normalized LMS Algorithm Degradation Due to Estimation Noise

The steady-state weight vector derived by either the least mean square (LMS) or normalized least mean square (NLMS) algorithms has random deviations from the optimum values. These deviations increase the steady-state residue power. A previous paper derived the LMS weight noise effects for a multiple sidelobe canceller (MSLC) application. This paper describes the NLMS weight noise effects. It is shown that for a thermal noise environment, the weight noise effect for the LMS algorithm is insignificant but is quite significant for the NLMS algorithm. Calculations for example noise plus interference environments imply that the NLMS weight noise effects are always larger than that for LMS.     

Analysis and Design of Series Resonant Converter by State-Plane Diagram

Analysis based on the state-plane diagram is given for series resonant converters operating in the frequency range 0.5 ? fs/fo ? 1.0. When the voltages and currents in the converter are normalized, design parameters take on special geometric meanings in the normalized state diagram. Examples of converter design using graphical methods are given for the cases of ? and ? control. Control characteristics of the converter operating in the continuous conduction mode are derived. The concept of the energy reflection coefficient is introduced as a measure of power transfer efficiency in the converter design.