An alternate algorithm for discrete-time filtering

The discrete-time Kalman filter is an optimal estimator for the states of a linear, stochastic system. It assumes that measurements are linear combinations of the states, and all disturbances are Gaussian. The influence diagram, a decision analysis tool that provides an algorithm for discrete-time filtering equivalent to the Kalman filter when the influence diagram represents Gaussian random variables, is discussed. The influence diagram algorithm is a factored form of the Kalman filter, similar to other factored forms such as the U-D filter. Compared with the Kalman filter, it offers improved numerical properties. Compared with other factored forms, it offers a reduced computational load     

Statistical analysis of experimental study results on low-cycle fatigue resistance for the EI698-VD high-temperature alloy

The results of low-cycle fatigue tests of smooth cylindrical specimens made of the EI698-VD nickel-base high-temperature alloy widely used in aircraft engine industry are considered statistically. The influence of such factors as an initial level of mechanical properties, operating time and temperature of tests is evaluated. The experimental data on low-cycle fatigue (LCF) are used when determining the cyclic life for disks.     

Robust wavelet neuro control for linear brushless motors

Design, simulation and experimental implementation of a wavelet basis function network learning controller for linear brushless dc motors (LBDCM) are considered. Stability robustness with position tracking is the primary concern. The proposed controller deals mainly with external disturbances, e.g. nonlinear friction force and payload variation in motion control of linear motors. It consists of two parts, one is a state feedback component, and the other one is a learning feedback component. The state feedback controller is designed on the basis of a simple linear model, and the learning feedback component is a wavelet neural controller. The attenuation effect of wavelet neural networks on friction force is first verified by the numerical method. The learning effect of wavelet neural networks on friction force is also shown in the numerical results. Then, a wavelet neural network is applied on a real LBDCM to on-line suppress the friction force, which may be variable due to the different lubrication. The effectiveness of the proposed control schemes is demonstrated by simulated and experimental results.     

Advances in signal processing technology for electronic warfare

The denial of effective communications by enemy forces during hostile military operations has been a primary concern for military commanders since the inception of radio communications on the battlefield before World War II. Since then, the electromagnetic environment has been in a constant state of evolution toward more sophisticated jam-resistant and convert forms of modulation. For example, exotic modulation techniques employing spread spectrum (SS) signaling are routinely used by our adversaries to provide their communication links an advantage over US and Allied jammers. These same spread spectrum modulation techniques are being refined to provide convert, low probability-of-intercept (LPI) features to the unintended interceptor. The thrust of this paper focuses on developments in the theory and algorithms for detection, characterization, and exploitation of advanced waveforms using new mathematical signal processing tools. Specifically, quadratic time-frequency signal representations, wavelet transforms, and cyclostationary signal processing are introduced. This overview demonstrates the importance of these advanced techniques in a clear and concise manner. Applications and future research activities are described     

Multiple moving target detection and trajectory estimation using a single SAR sensor

A novel methodology is presented for determining the velocity and location of multiple moving targets using a single strip-map synthetic aperture radar (SAR) sensor. The so-called azimuth position uncertainty problem is therefore solved. The method exploits the structure of the amplitude and phase modulations of the returned echo from a moving target in the Fourier domain. A crucial step in the whole processing scheme is a matched filtering, depending on the moving target parameters, that simultaneously accounts for range migration and compresses two-dimensional signatures into one-dimensional ones without losing moving target information. A generalized likelihood ratio test approach is adopted to detect moving targets and derive their trajectory parameters. The effectiveness of the method is illustrated with synthetic and real data covering a wide range of targets velocities and signal-to-clutter ratios (SCRs). Even in the case of parallel to platform moving target motion, the most unfavorable scenario, the proposed method yields good results for, roughly, SCR > 10 dB.     

PMHT: problems and some solutions

The probabilistic multihypothesis tracker (PMHT) is a target tracking algorithm of considerable theoretical elegance. In practice, its performance turns out to be at best similar to that of the probabilistic data association filter (PDAF); and since the implementation of the PDAF is less intense numerically the PMHT has been having a hard time finding acceptance. The PMHT's problems of nonadaptivity, narcissism, and over-hospitality to clutter are elicited in this work. The PMHT's main selling-point is its flexible and easily modifiable model, which we use to develop the "homothetic" PMHT; maneuver-based PMHTs, including those with separate and joint homothetic measurement models; a modified PMHT whose measurement/target association model is more similar to that of the PDAF; and PMHTs with eccentric and/or estimated measurement models. Ideally, "bottom line" would be a version of the PMHT with clear advantages over existing trackers. If the goal is of an accurate (in terms of mean square error (MSE)) track, then there are a number of versions for which this is available.     

Drop motion in a rotating immiscible liquid body

The interaction of liquids is an important part of many processes and is often used for such purposes as causing a separation of solution components by mass transfer between phases, allowing a chemical reaction between liquids or their components, providing direct contact heating or cooling, or creating emulsions. Containerless space processing may well involve the interaction of liquids in the form of drops. For example it may be desirable to form an alloy in space by merger of two or more drops. Encapsulation of a volatile liquid by a second less volatile and immiscible liquid might be a means for avoiding volatilization. Rotation of such systems would enhance mixing where desirable and/or provide means for drop management. In this study, single drop behavior in rotating liquid bodies is studied experimentally.     

Convective motions in liquid metals for material processings. Numerical simulation of oscillation regimes and effect of rotation

The paper is concerned with the numerical simulation and the analysis of some kinds of flow regimes which can develop in Bridgman and Czochralski systems for material processings. The flows in the liquid phase are investigated considering two-dimensional and axisymmetric models. The time-dependent regimes were studied for a zero-Prandtl-number fluid layer confined inside a two-dimensional cavity of aspect ratio (length-to-height) A=4, involving a stress-free upper surface and submitted to a horizontal temperature gradient. The range of Grashof number was varied up to the conditions at which the flow goes from oscillatory to chaotic type behaviours. The combined influence of the temperature gradients and of the rotations of the crucible and of the seed/crystal was investigated for a Czochralski model. The axisymmetric regimes were studied for a Pr_m=0.015 liquid melt confined inside a cylindrical crucible of aspect ratio (height-to-radius) A_m=2, and coupled to a viscous encapsulant liquid layer (10<Pr_e<1200) of aspect ratio A_e=0.5. A number of steady and (transient) time-dependent flow patterns are identified.     

Thermoluminescent dose measurements on-board Salyut type orbital stations.

A small, vibration- and shock-resistant thermoluminescent dosemeter /TLD/ system--named PILLE--was developed at the Health Physics Department of the Central Research Institute for Physics, Budapest, to measure the cosmic radiation dose on board orbital stations. The first on-board measurements with this system were performed /by B. Farkas, the Hungarian astronaut/, on the Salyut-6 space station in 1980. The same instrument was used by other crews in the following years. Doses measured at different sites in Salyut-6 are presented. The dose rates varied from 0.07 to 0.11 mGy.day-1. After the first cosmic measurements, the system was further developed. The minimum detectable dose of the new TLD system is 1 microGy, i.e. less by on order of magnitude than that of the former system. The self-irradiation dose rate of the TLD bulbs is also reduced--by more than one order of magnitude--to 10 nGy.h-1, by the use of potassium-free glass for the bulb envelope. This new type of PILLE TLD system is currently on-board Salyut-7. The dose rates /0.12-0.23 mGy.day-1/ measured in 1983 are presented in detail.