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IEEE Regional Conference on Aerospace control Systems

作者： T.W. Hilands S.C.A. Thomopoulos Applied Research Laboratory Pennsylvania State University University Park PA USA Decision Control Systems Laboratory Department of Electrical and Computer Engineering Pennsylvania State University University Park PA USA

This paper addresses the problem of multi sensor detection and high resolution signal parameter estimation using joint maximum a posteriori detection and high order nonlinear filtering techniques. The model-based fusion approach offers the potential for increased target resolution in range/azimuth space. The technique employs joint detection/estimation filters (JDEF) for target detection and parameter localization. The JDEF approach segments the aggregate nonlinear model over the entire target resolution space into subcells. This partitioning leads to extremely accurtate detection and parameter estimation. The proposed JDEF approach has a built-in capability for automatic data alignment from multiple sensors, and can be used for centralized, noncentralized, and distributed data fusion.

关键词： Sensor arrays Sensor fusion Radar tracking Phased arrays Delay estimation Phase estimation Delay effects Sea measurements Laboratories Signal resolution

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High Resolution Target Range Estimation in the Presence of Multipath Using JDEF

High Resolution Target Range Estimation in the Presence of M...

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IEEE Regional Conference on Aerospace control Systems

作者： M.D. Reger S.C.A. Thomopoulos Applied Research Laboratory Pennsylvania State University University Park PA USA Decision and Control Systems Laboratory Department of Electrical and Computer Engineering Pennsylvania State University University Park PA USA

The Joint Detection/Estimation Filter (JDEF) [1,2] can be utilized to improve the performance of a single Extended Kalmart Filter (EKF) when the problem of estimation involves a large initial variance. In this case the JDEF is used to estimate the presence and location of a point target when the received signal is corrupted by multipath. In the formulation of the problem it was assumed that both the target and sensor were stationary and that there was an equal probability of the point target being present or absent along a center look direction. This implementation of the JDEF proved to be quite successful and can be easily expanded to estimate a larger number of unknown parameters.

关键词： Filters State estimation Laboratories Delay estimation Underwater tracking Mean square error methods control systems Sensor phenomena and characterization Sensor systems Gaussian noise

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High Order Filters for Estimation in Non-Gaussian Noise

High Order Filters for Estimation in Non-Gaussian Noise

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American control Conference (ACC)

作者： Stelios C. A. Thomopoulos Thomas W. Hilands Decision and Control Systems Laboratory Department of Electrical and Computer Engineering Pennsylvania State University University Park PA USA Applied Research Laboratory Pennsylvania State University University Park PA USA

In this paper high order vector filter equations are developed for estimation in non-Gaussian noise. The difference between the filters developed here and the standard Kalman filter is that the filter equation contains nonlinear functions of the innovations process. These filters are general in that the initial state covariance, the measurement noise covariance, and the process noise covariance can all have non-Gaussian distributions. Two filter structures are developed. The first filter is designed for systems with asymmetric probability densities. The second is designed for systems with symmetric probability densities. Experimental evaluation of these filters for estimation in non-Gaussian noise, formed from Gaussian sum distributions, shows that these filters perform much better than the standard Kalman filter, and close to the optimal Bayesian estimator.

关键词： Filters Bayesian methods Noise measurement State estimation Laboratories Nonlinear equations Technological innovation Vectors control systems Standards development

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High Resolution Model Order Selection and Parameter Estimation Using JDEF (Joint Detection/Estimation Filter)

High Resolution Model Order Selection and Parameter Estimati...

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IEEE Regional Conference on Aerospace control Systems

作者： S.C.A. Thomopoulos K. Ramaswamy G. Rajagopal T.W. Hilands Decision & Control Systems Laboratory Department of Electrical & Computer Engineering Pennsylvania State University University Park PA USA Applied Research Laboratory Pennsylvania State University University Park PA USA

The problem of model order selection in the presence of parametric uncertainty is considered. A high resolution joint detection/estimation filter is used to detect the correct order of the model and estimate the signa... 详细信息

关键词： Parameter estimation Radar detection Acoustic signal detection Filters Additive noise Predictive models Laboratories Mathematical model State estimation Higher order statistics

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Nonlinear Adaptive Joint Detection/Estimation for Multi-Radar Data Fusion

Nonlinear Adaptive Joint Detection/Estimation for Multi-Rada...

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American control Conference (ACC)

作者： Thomas W. Hilands Stelios C. A. Thomopoulos Applied Research Laboratory Pennsylvania State University University Park PA USA Decision and Control Systems Laboratory Department of Electrical and Computer Engineering Pennsylvania State University University Park PA USA

This paper addresses the problem of multisensor detection and high resolution signal parameter estimation using joint maximum a posteriori detection and high order nonlinear filtering techniques. The model-based fusion approach offers the potential for increased target resolution in range/azimuth space. The technique employs joint detection/estimation (JDE) filters for target detection and target parameter localization. The JDE approach segments the aggregate nonlinear model over the entire target resolution space into resolution subcells. This partitioning leads to extremely accurtate detection and parameter estimation. The proposed JDE approach has a built-in capability for automatic data alignment from multiple sensors, and can be used for centralized, noncentralized, and distributed data fusion.

关键词： Sensor arrays Parameter estimation Phased arrays State estimation Sensor fusion Radar tracking Clutter Delay effects Sea measurements Signal resolution

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An approach to the direct analysis of transient stability

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European Transactions on Electrical Power 1993年第3期3卷 241-248页

作者： Djukanovic, M.B. Sobajic, D.J. Pao, Y.‐H. Miodrag B. Djukanovic (1959) received his B.S. M.Sc. and Ph.D. degrees in Electrical Engineering from the University of Belgrade/Yugoslavia in 1982 1985 and 1992 respectively specializing in electric power systems. In 1984 he joined the Electrical Engineering Institute “Nikola Tesla” in Belgrade where he was working on the scientific studies in the field of power systems planning operation and control. In 1985 and 1990 he was appointed as a research scholar at the Royal Institute of Technology Stockholm and Case Western Reserve University Cleveland Ohio. His major in- terests are in the area of power system analysis steady-state and dynamic security and application of neural networks in electric power systems. (Electrical Engineering Institute “Nicola Tesla” ul. Koste Glavinica 8A YU-11000 Belgrad T +3811/2351-619 Fax + 3811/2351-823) Dejan J. Sobajic (1949) received the B.S.E.E. and the M.S.E.E. degrees from the University of Belgrade/Yugoslavia in 1972 and 1976 respectively and the Ph.D. degree from Case Western Reserve University Cleveland Ohio in 1988. At present he is with the Department of Electrical Engineering and Applied Physics Case Western Reserve University Cleveland. He is also the Engineering Manager of A1 WARE Inc. Cleveland. His current research interests include power system operation and control neuralnet systems and adaptive control. He is a member of the IEEE Task Force on Neural-Network Applications in Power Systems and of the IEEE Intelligent Controls Committee. He is the Chairman of the International Neural-Networks Society Special Interest Group on Power Engineering. (Case Western Reserve University Department of Electrial Engineering and Computer Sciences Glennan Building Ohio 44 106 USA T + 1216/421-2380 Fax +1216/368-8776) Yoh-Han Pao (1922) has been a Professor of Electrical Engineering and Computer Science at Case Westem Reserve University (CWRU) Cleveland Ohio since 1967. He has served as chairman of the University's Electrical Engineering Department

The Transient Energy Function (TEF) method has been intensely investigated over the last decade as a reliable and accurate tool for transient stability assessment of multimachine power systems. In this paper we propose the Potential Energy Boundary Surface (PEBS) based method for direct analysis of transient stability. The critical value of transient energy and the Critical Clearing Time (T_CCT) are evaluated without the need for successive calculation and memorization of the system kinetic and potential energy values along the sustained fault trajectory. The method is used for determination of output features in the training phase of the neural‐net based transient security assessment. The proposed approach is tested on the well‐known ten‐generator New England test system demonstrating the validity and accuracy of obtained results. Copyright © 1993 John Wiley & Sons, Ltd.

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Joint detection/estimation for modal order selection in Gaussian and nonGaussian noise

Joint detection/estimation for modal order selection in Gaus...

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MILCOM, Military Communications Conference

作者： S.C.A. Thomopoulos T.W. Hilands Decision and Control Systems Laboratory Department of Electrical and Computer Engineering Pennsylvania State University University Park PA USA Applied Research Laboratory Pennsylvania State University University Park PA USA

The authors present a general approach to determining the number of sinusoids present in measurements corrupted by additive white Gaussian and nonGaussian noise. The approach involves the simultaneous application of maximum a posteriori detection and nonlinear estimation using either the extended Kalman filter when the noise is Gaussian, or the extended high order filter when the noise is nonGaussian. The problem is formulated as a multiple hypothesis testing problem with assumed known a priori probabilities for each hypothesis. The advantage of the approach lies in the potential to accommodate time-varying as well as time-invariant parameters in the measurement model. Experimental evaluation of the approach demonstrates excellent performance in selecting the correct model order and estimating the system parameters even for signal-to-noise ratios as low as -5 dB.< >

关键词： Gaussian noise State estimation Noise measurement Autocorrelation Matrix decomposition Recursive estimation control systems Additive noise Additive white noise Application software

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Nonlinear filtering methods for harmonic retrieval

Nonlinear filtering methods for harmonic retrieval

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MILCOM, Military Communications Conference

作者： T.W. Hilands S.C.A. Thomopoulos Applied Research Laboratory Pennsylvania State University University Park PA USA Decision and Control Systems Laboratory Department of Electrical and Computer Engineering Pennsylvania State University University Park PA USA

The authors address the problem of high-resolution parameter estimation of superimposed sinusoids using nonlinear filtering techniques. Six separate nonlinear filters are evaluated for the estimation of the parameters of sinusoids in white and colored Gaussian noise. Experimental evaluation demonstrates that the nonlinear filters perform very satisfactorily (close to the Cramer-Rao bound) for reasonable values of the initial estimation error. A major advantage of using nonlinear filtering methods for harmonic retrieval is that the filters can be applied to time-varying process models as well.< >

关键词： Filtering Power harmonic filters Nonlinear filters Noise measurement Parameter estimation Equations Gaussian noise Frequency estimation Damping White noise

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Nonlinear adaptive detection/estimation for single and multiple radar processing

Nonlinear adaptive detection/estimation for single and multi...

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MILCOM, Military Communications Conference

作者： S.C.A. Thomopoulos T.W. Hilands Department of Electrical and Computer Engineering Decision and Control Systems Laboratory Pennsylvania State University University Park PA USA Applied Research Laboratory Pennsylvania State University University Park PA USA

A nonlinear adaptive detector/estimator is introduced for single and multiple radar data processing. The problem of target detection from returns of monostatic radar(s) is formulated as a nonlinear joint detection/estimation problem on the unknown parameters in the signal return. The problems of detecting the target and estimating its parameters are considered jointly. A bank of spatially and temporally localized nonlinear filters is used to estimate the a posteriori likelihood of the existence of the target in a given space-time resolution cell. Within a given cell, the localized filters are used to produce refined spatial estimates of the target parameters. A decision logic is used to decide on the existence of a target within any given resolution cell based on the a posteriori estimates obtained from the likelihood functions. Simulation results show excellent detection capabilities and excellent resolution in target parameter estimation for both single and multiple sensor data.< >

关键词： Radar detection Spatial resolution Parameter estimation Detectors Data processing Object detection Nonlinear filters Signal resolution Refining Logic

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Harmonic insertion in PWM inverter drive schemes

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European Transactions on Electrical Power 1992年第3期2卷 143-151页

作者： Theocharis, J. Petridis, V. Dr.-Ing. John Theocharis (1956) graduated as an Electrical Engineer from Aristotelian University of Thessaloniki.Greece in 1980. From 1980 to 1985 he has been with the scientific staff of the Department of Electrical Engineering at the Aristotelian University where he received the Ph.D. degree in 1985. Since 1986 he is working as a lecturer and in 1990 he became assistant professor at the Department of Electronics and Computer Engineering in the m e university. His research activities include control power electronics and electrical motor drives. Recently he is working with the Neural Network Systems with applications to field oriented control problems. Aristotelian University of Thessaloniki School of Engineering Faculty of Electrical Engineering Dept. of Electronics & Computer Engineering P.O. Box 438 GR-Thessalonikil/Greece.T+3131/219784Fax + 3031/274868) Prof. Dr.-Ing. Vasilis Petridis (1946) graduated from National Technical University of Athens Greece in 1969.He obtained the M.Sc. and the Ph.D. in electronics and systems from the University of London in 1970 and 1974. respectively. H i s interests include applied automatic control neural networks drives dynamic systems robotics etc. He is currently professor in the Department of Electronics and Computer Engineering of the University of Thessaloniki. (Aristotelian University of Thessaloniki. School of EngineeringFaculty of Electrical Engineering Dept. of Electronics & Computer Engineering P.O. Box 438. GR-ThessaloniW Greece T+3031/219784.Fax+3031/274868)

The procedure of harmonic insertion is generalized in this paper. Analytical expressions of the voltage spectra are derived. The insertion of the 3rd harmonic to the modulating signal, which is of particular interest, is considered as a special case. It is demonstrated in this case that the fundamental harmonic component of the phase and the line‐to‐line voltage is not affected by the insertion of the 3rd harmonic for sufficiently high values of the chopping ratio. However it has been shown that the higher harmonic spectrum is significantly improved as compared to the case of pure sinusoidal modulation. For different values of the fundamental component the optimal values of the amplitude of the third harmonic to be inserted have been calculated so that the distortion factor of the higher harmonic spectrum is minimized. Other cases of harmonic insertion are also considered which provide spectrum efficiency improvement. Experimental results are given which have been obtained by means of a microcomputer controlled PWM generator constructed for this purpose. Copyright © 1992 John Wiley & Sons, Ltd.

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