The Low Metallicity Tail of the Halo Metallicity Distribution Function

Ongoing spectroscopy and photometry of stars selected in the HK objective-prism/interference-filter survey of Beers and colleagues has resulted in the identification of many hundreds of additional stars in the halo (and possibly the thick disk) of the Galaxy with abundances [Fe/H] -2.0. A new calibration of the technique for estimation of metal abundance based on a CaII K index as a function of broadband B - V color is applied to obtain metallicities for stars observed with the SSO 2.3m and INT 2.5m telescopes. This new data is combined with other samples of extremely metal-deficient stars (Ryan and Norris, 1991a; Beers et al., 1992; Carney et al., 1994) to form a large database of objects of low metallicity. The combined sample is examined and compared with expectations derived from a Simple Model of Galactic chemical evolution. There appears to be a statistically-significant deficit of stars more metal-weak than [Fe/H] = -3.0. An abundance of [Fe/H] -4.0 can be taken as the low-metallicity limit for presently-observable stars in the Galaxy.     

Output of a Balanced Frequency Discriminator Driven by a Sine Wave and Gaussian Noise

The output of a realizable balanced frequency discriminator is calculated for an input consisting of a sine wave plus Gaussian noise. Explicit autocorrelation and power spectra are found for one practical embodiment of the discriminator for various input carrier-to-noise ratios, with the carrier tuned to center frequency and also off-center. The formulas also permit the calculation of the output for the case of a spectrum of noise slowly swept through the discriminator. Although qualitatively similar to results previously obtained with an ideal discriminator, substantial differences are also found. Measurements are made that closely verified the theoretical results. No limiting is assumed.     

Ion Acoustic Waves in the Heliosphere

Observations of ion acoustic waves in the solar wind during the first and second orbit of the Ulysses spacecraft are presented. The observations show variations of the wave activity with the heliolatitude and with the phase of the solar cycle. The interrelationships between the wave intensity and the electron heat flux and the ratio of electron to proton temperature, T _e/T _p, are examined. This revised version was published online in August 2006 with corrections to the Cover Date.     

The FAST Satellite Fields Instrument

We describe the electric field sensors and electric and magnetic field signal processing on the FAST (Fast Auroral SnapshoT) satellite. The FAST satellite was designed to make high time resolution observations of particles and electromagnetic fields in the auroral zone to study small-scale plasma interactions in the auroral acceleration region. The DC and AC electric fields are measured with three-axis dipole antennas with 56 m, 8 m, and 5 m baselines. A three-axis flux-gate magnetometer measures the DC magnetic field and a three-axis search coil measures the AC magnetic field. A central signal processing system receives all signals from the electric and magnetic field sensors. Spectral coverage is from DC to 4 MHz. There are several types of processed data. Survey data are continuous over the auroral zone and have full-orbit coverage for fluxgate magnetometer data. Burst data include a few minutes of a selected region of the auroral zone at the highest time resolution. A subset of the burst data, high speed burst memory data, are waveform data at 2×10⁶ sample s^–1. Electric field and magnetic field data are primarily waveforms and power spectral density as a function of frequency and time. There are also various types of focused data processing, including cross-spectral analysis, fine-frequency plasma wave tracking, high-frequency polarity measurement, and wave-particle correlations.     

Analysis of a Class of Nonlinear Sampled-Data Systems with a Gaussian Input Signal

The problem treated here is the analysis of a class of nonlinear sampled-data systems with a Gaussian input signal. The nonlinear element is a symmetrical limiter (memoryless device) that feeds the linear element. Preceding the limiter is a sampler and zero-order hold unit for data reconstruction. The analysis is predicated on finding an equivalent gain for the nonlinear element such that the mean-square error is a minimum. The nonlinearity is thus replaced by a linear component and the system is then analyzed by conventional techniques. It is also shown that for appropriate sampling rates the sampled-data system is equivalent to a continuous system due to the action of the sampler-hold combination. All calculations pertaining to the limiter input signal require the use of a transfer function that is interior to the feedback loop. However, in developing this transfer function, the overall system is considered so that the system output may be evaluated after the value of equivalent gain has been found.     

A Hybrid Navigation Concept Using a Spinning Satellite?Borne Interferometer and Self?Contained Equipment

This paper analyzes a hybrid navigation concept that uses signals from a radio interferometer mounted on a spinning geostationary satellite, preliminary position estimates from self-contained equipment, and stored a priori information on the past performance of this equipment. The craft-borne processor, optimum in the maximum a posteriori (MAP) sense, is designed to estimate position coordinates using only the incoming radio signals, although improved estimates result if the other two items are available. An error analysis starts with the derivation of an estimation error covariance matrix, whose elements depend on additive receiver noise and the physical parameters of the system. A minimum 1? estimation error in position is obtained by trading off these parameters. The effects of other major error sources, such as tropospheric phase fluctuations, multipath, and craft altitude uncertainty, are added to the estimation error to give a total 1? position error on the order of 3.7 to 5.6 km.     

Analysis of geometrically nonlinear shells of revolution based on the finite element method with the vector interpolation of desired quantities

In this paper, we present an algorithm for geometrically nonlinear finite element analysis of the shells of revolution. Use is made of the most proper algorithms for vector interpolation of displacements through the nodal unknowns and an efficient algorithm for obtaining the stress-strain increment relation at a step of loading. By comparing the results of analyzing a geometrically nonlinear shell of revolution obtained on the basis of the ANSYS software with the scalar interpolation of displacements with those obtained on the basis of an author-developed finite element, it has been shown that application of the FEM vector displacement interpolation leads to increasing the accuracy of the finite element solutions in analyzing the stress-strain state of the geometrically nonlinear shells.     

The Freja wave and plasma density experiment

The Wave Experiment, F4, on the Swedish/German satelliteFreja, is designed to measure the electric wave fields up to 4 MHz, the magnetic wave fields up to 16 kHz and the plasma density and its relative variations up to 2 kHz. Six wave signals and four density probe signals can be measured simultaneously. The wave forms of all signals are transmitted to ground without any analysis onboard. The limited TM allocation does not allow continuous sampling of the wave signals, so normally the measurements are made in snapshots of various lengths dependent on sampling frequency, etc. Continuous sampling can be made for shorter time periods by using a 6 Mbyte memory as a buffer.     

Synergism of binocular and motion stereo for passive ranging

Range measurements to objects in the world relative to mobile platforms such as ground or air vehicles are critical for visually aided navigation and obstacle detection/avoidance. An approach is presented that consists of a synergistic combination of two types of passive ranging method: binocular stereo and motion stereo. We show a new way to model the errors in binocular and motion stereo in conjunction with an inertial navigation system (INS) and derive the appropriate Kalman filter to refine the estimates from these two stereo ranging techniques. We present results using laboratory images that show that refined estimates can be optimally combined to give range values which are more accurate than any one of the individual estimates from binocular and motion stereo. By incorporating a blending filter, the approach has the potential of providing accurate, dense range measurements for all the pixels in the field of view (FOV)