Communications and radio determination system using twogeostationary satellites. I. System and experiments

We developed two types of hybrid terminals that can provide both satellite communication and position determination services in one system. One terminal uses the single channel per carrier (SCPC) technique and the other uses the spread spectrum (SS) technique. To evaluate the performance of the two systems, we carried out experiments in Japan and in the Pacific Ocean using two geostationary satellites, ETS-V (150°E) and Inmarsat (180°E). The ranging accuracy between the mobile terminals and the base station via the satellites was found to be about 200 m using the SCPC system and about 10 m using the SS system. The measured positioning accuracy was about 1 km in the SCPC system and about 600 m in the SS system when experiments were carried out near Japan. The experimental results show that the positioning errors were mainly caused by the orbital determination errors of the two satellites. Presented here are the configurations and features of the SCPC and SS terminals, the experimental system, and the experimental results     

Analysis and design of (LC)(LC)-type series-parallel resonantconverter

A series-parallel resonant converter employing (LC)(LC)-type tank circuit operating in lagging power factor (PF) mode is presented and analyzed using complex ac circuit analysis. Design curves are obtained and the converter is optimized under certain constraints. Detailed Space Integrated Control Experiment (SPICE) simulation results are presented to evaluate the performance of the designed converter under varying load conditions. Results obtained from an experimental converter are also presented. The results obtained from the theory, SPICE simulation, and the experimental converter are compared. The proposed converter has high efficiency from full load to very light load (<10%). Switching frequency variation required for a wide change in the load (near load open circuit to full load) is narrow compared with the series resonant converter (SRC)     

Computer simulation of IGBT losses in PFC circuits

An analysis is presented that forms the basis for an algorithm for calculating the IGBT losses in a power factor correction (PFC) circuit. The method employs experimental data from an off-line test circuit that closely resembles the switching conditions in the actual PFC. This technique provides calculated values of both the conduction and switching losses of the main transistor in a boost-type PFC circuit. Results for a 6 kW PFC are included     

Robust algorithm for combating look direction error problems

A simple and fast zero tracking algorithm for adaptive arrays with large look direction errors is presented and investigated. Basically, the algorithm is based on adjusting the complex zeroes of a power inversion array in a time-multiplexed manner to track all the sources in the environment. To preserve the desired signal which is supposed to be closest to the look direction of 0°, the algorithm removes the zero with the shortest distance to e^j0 so that the directional response consists of only nulls steered at the jammers. When compared with the least mean square (LMS) algorithm employing zeroth and first-order look direction constraints, the new algorithm has about the same implementation complexity, is considerably faster, and possesses a much better signal-to-noise ratio (SNR) performance when the look direction is erroneous     

Adaptive image segmentation using genetic and hybrid search methods

This paper describes an adaptive approach for the important image processing problem of image segmentation that relies on learning from experience to adapt and improve the segmentation performance. The adaptive image segmentation system incorporates a feedback loop consisting of a machine learning subsystem, an image segmentation algorithm, and an evaluation component which determines segmentation quality. The machine learning component is based on genetic adaptation and uses (separately) a pure genetic algorithm (GA) and a hybrid of GA and hill climbing (HC). When the learning subsystem is based on pure genetics, the corresponding evaluation component is based on a vector of evaluation criteria. For the hybrid case, the system employs a scalar evaluation measure which is a weighted combination of the different criteria. Experimental results for pure genetic and hybrid search methods are presented using a representative database of outdoor TV imagery. The multiobjective optimization demonstrates the ability of the adaptive image segmentation system to provide high quality segmentation results in a minimal number of generations     

Neural controllers for systems with unknown dynamics

This study presents a methodology for specifying a neural controller for a system about which no a priori model information is available. The neural design presumes that a finite duration input/output (I/O) histogram on the system is available. The design procedure extracts from the histogram sufficient information to specify the neural feedback controller. The resultant controller will drive the system along a general output reference profile (unknown during the design). The resultant controller also exhibits the capability of disturbance rejection and the capacity to stabilize unstable plants     

Presupernova evolution of the most massive stars

Taking as example a 60M _⊙ star of solar metallicity, the state of the art of model calculations for very massive, from the main sequence to the supernova stage, is reviewed. It is argued that — due to the simple internal structure of Wolf-Rayet stars — the post main sequence evolutionary phases are currently those which are better understood. A brief discussion of the supernova outcome from very massive stars is given. Then, the more uncertain main sequence evolution is discussed. A first attempt to incorporate results about pulsational instabilities of very massive stars in stellar evolutionary calculations is performed. On its basis, a new type of evolutionary sequence for very massive stars is obtained, namely O-star → Of-star → H-rich WNL → LBV → H-poor WNL → WNE → WC → SN. This scenario is shown to correspond better to many observed properties of very massive stars than the standard one. It includes a model for the prototype LBV P Cygni.     

Wind asymmetries in massive stars

We are in the process of surveying the linear polarization in luminous, early-type stars. We here report on new observations of the B [e] stars S 18 and R 50, and of the Luminous Blue Variables HR Car, R 143, and HD 160529. Together with previously published data, these observations provide clear evidence for the presence of intrinsic polarization in 1 B[e] star (HD 34664) and in 5 LBVs ( Car, P Cyg, R 127, AG Car, and HR Car). The data indicate that anisotropic stellar winds are a common occurrence among massive stars in these particular evolutionary stages. For such stars, mass-loss rates estimated using the assumption of a spherical, homogeneous and stationary outflow may be in error.     

The impact of semi-convection and overshooting on the surface abundances in massive stars

We analyse the effects of semi-convection and overshooting on the predicted surface abundances after the first and second dredge-ups in 15 and 20 M Pop. I stars. Overshooting is applied either to the core boundary or to the boundaries of all convective zones. It is shown that the surface abundances are sensitive to the mixing scheme adopted in the interior. The models including semi-convection lead to lower¹²C/¹³C ratios than the other mixing schemes, while models with overshooting predict higher enhancements of sodium at the surface.     

A modified Gaussian sum approach to estimation of non-Gaussiansignals

A Gaussian sum estimation algorithm has previously been developed to deal with noise processes that are non-Gaussian. Inherent in this algorithm is a serious growing memory problem that causes the number of terms in the Gaussian sum to increase exponentially at each iteration. A modified Gaussian sum estimation algorithm using an adaptive filter is developed that avoids the growing memory problem of the previous algorithm while providing effective state estimation. The adaptive filter is comprised of a fixed set of estimators operating in parallel with each individual estimate possessing its own corresponding weighting term. A simulation example illustrates the new non-Gaussian estimation technique