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     

The Apollo SWC Experiment: Results,Conclusions, Consequences

Space Science Reviews - The Apollo Solar Wind Composition (SWC) experiment was designed to measure elemental and isotopic abundances of the light noble gases in the solar wind, and to investigate...     

Variations of the magnetic fields in large solar flares

We present preliminary results from high resolution observations obtained with the Michelson Doppler Imager (MDI) instrument on the SOHO of two large solar flares of 14 July 2000 and 24 November 2000. We show that rapid variations of the line-of-sight magnetic field occured on a time scale of a few minutes during the flare explosions. The reversibility/irreversibility of the magnetic field of both active regions is a very good tool for understanding how the magnetic energy is released in these flares. The observed sharp increase of the magnetic energy density at the time of maximum of the solar flare could involve an unknown component which deposited supplementary energy into the system. This revised version was published online in August 2006 with corrections to the Cover Date.     

Huygens Probe Aerosol Collector Pyrolyser Experiment

ACP's main objective is the chemical analysis of the aerosols in Titan's atmosphere. For this purpose, it will sample the aerosols during descent and prepare the collected matter (by evaporation, pyrolysis and gas products transfer) for analysis by the Huygens Gas Chromatograph Mass Spectrometer (GCMS). A sampling system is required for sampling the aerosols in the 135'32 km and 22'17 km altitude regions of Titan's atmosphere. A pump unit is used to force the gas flow through a filter. In its sampling position, the filter front face extends a few mm beyond the inlet tube. The oven is a pyrolysis furnace where a heating element can heat the filter and hence the sampled aerosols to 250 °C or 600 °C. The oven contains the filter, which has a thimble-like shape (height 28 mm). For transferring effluent gas and pyrolysis products to GCMS, the carrier gas is a labeled nitrogen ¹⁵N₂, to avoid unwanted secondary reactions with Titan's atmospheric nitrogen. Aeraulic tests under cold temperature conditions were conducted by using a cold gas test system developed by ONERA. The objective of the test was to demonstrate the functional ability of the instrument during the descent of the probe and to understand its thermal behavior, that is to test the performance of all its components, pump unit and mechanisms. In order to validate ACP's scientific performance, pyrolysis tests were conducted at LISA on solid phase material synthesized from experimental simulation. The chromatogram obtained by GCMS analysis shows many organic compounds. Some GC peaks appear clearly from the total mass spectra, with specific ions well identified thanks to the very high sensitivity of the mass spectrometer. The program selected for calibrating the flight model is directly linked to the GCMS calibration plan. In order not to pollute the two flight models with products of solid samples such as tholins, we excluded any direct pyrolysis tests through the ACP oven during the first phase of the calibration. Post probe descent simulation of flight results are planned, using the much representative GCMS and ACP spare models. This revised version was published online in August 2006 with corrections to the Cover Date.     

Acceleration of the solar wind

In this review, we discuss critically recent research on the acceleration of the solar wind, giving emphasis to high-speed solar wind streams emanating from solar coronal holes. We first explain why thermally driven wind models constrained by solar and interplanetary observations encounter substantial difficulties in explaining high speed streams. Then, through a general discussion of energy addition to the solar wind above the coronal base, we indicate a possible resolution of these difficulties. Finally, we consider the question of what role MHD waves might play in transporting energy through the solar atmosphere and depositing it in the solar wind, and we conclude by examining, in a simple way, the specific mechanism of solar wind acceleration by Alfvén waves and the related problem of accelerating massive stellar winds with Alfvén waves.Paper presented at the IX-th Lindau Workshop The Source Region of the Solar Wind.On leave from the Auroral Observatory, Institute of Mathematical and Physical Sciences, University of Tromsø, N-9001 Tromsø, Norway.The National Center for Atmospheric Research is sponsored by the National Science Foundation.     

Statistical Technique for Radar Amplitude Calibration

A statistical technique for amplitude calibration of radar systems is presented. As distinct from the input-output crosscorrelation measurement of a linear system impulse response [1], this technique measures the amplitude transfer function of a memoryless, nonlinear system. A generalized theory is developed and calibration accuracy bounds are derived. Used in the calibration of a modern pulsed radar, the technique is compared with conventional reference pulse calibration. The relative merits of the deterministic and statistical approaches are compared.     

The Galileo Dust Detector

The Galileo Dust Detector is intended to provide direct observations of dust grains with masses between 10^-19 and 10^-9 kg in interplanetary space and in the Jovian system, to investigate their physical and dynamical properties as functions of the distances to the Sun, to Jupiter and to its satellites, to study its interaction with the Galilean satellites and the Jovian magnetosphere. Surface phenomena of the satellites (like albedo variations), which might be effects of meteoroid impacts will be compared with the dust environment. Electric charges of particulate matter in the magnetosphere and its consequences will be studied; e.g., the effects of the magnetic field on the trajectories of dust particles and fragmentation of particles due to electrostatic disruption. The investigation is performed with an instrument that measures the mass, speed, flight direction and electric charge of individual dust particles. It is a multicoincidence detector with a mass sensitivity 10⁶ times higher than that of previous in-situ experiments which measured dust in the outer solar system. The instrument weighs 4.2 kg, consumes 2.4 W, and has a normal data transmission rate of 24 bits s^-1 in nominal spacecraft tracking mode. On December 29, 1989 the instrument was switched-on. After the instrument had been configured to flight conditions cruise science data collection started immediately. In the period to May 18, 1990 at least 168 dust impacts have been recorded. For 81 of these dust grains masses and impact speeds have been determined. First flux values are given.     

An optimum filter for direct A/D conversion

The author describes a design procedure to find the optimum finite-impulse-response (FIR) filter coefficients when the characteristics of the bandpass filter preceding the analog-to-digital (A/D) converter are known. A simulation of direct A/D conversion performance shows the improvement over the filter coefficients designed to minimize the maximum error over a specified band of frequencies. DC cancellation may be added to the process with very little change in the coefficients of the optimum FIR filter or its performance.<>     

Stochastic Dynamic System Suboptimal Control with Uncertain Parameters

The control of a linear system with random coefficients is studied here. The cost function is of a quadratic form and the random coefficients are assumed to be partially observable by the controller. By means of the stochastic Bellman equation, the optimal control of stochastic dynamic models with partially observable coefficients is derived. The optimal control is shown to be a linear function of the observable states and a nonlinear function of random parameters. The theory is applied to an optimal control design of an aircraft landing in wind gust.     

State Estimation and Divergence Analysis

A growing memory discrete dynamic model for performing temporal extrapolations along a predetermined path in a random field is presented. This dynamic model is used to drive a linear system that is itself driven by discrete white noise. The coupled system is used to derive a state estimation scheme that recursively processes noisy measurements of the system. In addition, using the aforementioned dynamic model as a reference (truth) model, the authors develop a covariance analysis to measure the estimation errors that occur when the dynamics along the path through the field are modeled as a Markov linear model and state estimation is performed using discrete Kalman filtering. The performance evaluation of an inertial navigation system influenced by the Earth's gravity field aboard a maneuvering ship is provided as a specific illustrative example.