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17th conference on signal and data processing of small targets

作者： Farrell, MD Mersereau, RM Georgia Inst Technol Ctr Signal & Image Proc Atlanta GA 30332 USA

ISBN: (纸本)0819459186

Adaptive techniques for detecting small or difficult targets in the midst of high noise and/or clutter have a rich history in the radar array processing community. However, the utility of these schemes is only beginning to be realized for multichannel electro-optical techniques, specifically hyperspectral imaging (HSI). the data products generated by hyperspectral sensors differ greatly from those of radar and sonar arrays, yet recent studies using HSI data have offered promising results for modified versions of common adaptive detectors. In this paper, we compare a series popular adaptive detection schemes applied to HSI data for the task of land mine detection. Experiments using real hyperspectral image cubes, not Simulations, are performed with data from both the visible-SWIR and LWIR regions. Results are presented for different mine types in a variety of scenes.

关键词： adaptive detection array processing hyperspectral imaging land mines

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Bayesian approach to avoiding track seduction

Bayesian approach to avoiding track seduction

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14th conference on signal and data processing of small targets

作者： Salmond, DJ Everett, NO QinetiQ Farnborough GU14 0LX Hants England

ISBN: (纸本)0819444782

the problem of maintaining track on a primary target in the presence spurious objects is addressed. Recursive and batch filtering approaches are developed. For the recursive approach, a Bayesian track splitting filter is derived which spawns candidate tracks if there is a possibility of measurement misassociation. the filter evaluates the probability of each candidate track being associated with the primary target. the batch filter is a Markov-chain Monte Carlo (MCMC) algorithm which fits the observed data sequence to models of target dynamics and measurement-track association. Simulation results are presented.

关键词： Bayesian methods target tracking multiple targets JPDAF MCMC

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Target selection using neural networks

Target selection using neural networks

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14th conference on signal and data processing of small targets

作者： Özener, MS Yardimci, Y Univ Enformat Enstitusu Orta Dogu Tekn TR-06351 Ankara Turkey

ISBN: (纸本)0819444782

Target selection is the task of assigning a value or priority to various targets in a scenario. this priority is usually determined by the threat the target poses on the defender in addition to its vulnerability to possible measures to be taken by the defender. In this study, we describe a target selection technique based on neural networks. the utility or value of each target is assumed to be an unknown function acting on certain features of the target such as size, intensity, speed and direction of movement. Neural networks used in the context of function estimation is a viable candidate for determining this unknown function for generating target priorities. Various. neural network configurations are examined and simulation results are presented.

关键词： Neural networks Target detection Neurons Ranging signal processing Image processing Infrared imaging Infrared radiation Sensors databases

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Background modeling and target segmentation via modified Kalman filtering

Background modeling and target segmentation via modified Kal...

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16th conference on signal and data processing of small targets

作者： Searle, SJ Univ Adelaide Sch Elect & Elect Engn CSSIP Adelaide SA 5005 Australia

ISBN: (纸本)081945351X

In target detection and tracking applications with imagery data taken from a moving camera platform, it is necessary to segment potential targets in each image frame. this is typically done by preprocessing individual images to exploit some known attribute about the data. Often these methods make many false detections, particularly in the presence of additive noise, and the results thus require significant post-processing. A means of estimating the background in the imagery sequence under the formalism of the Kalman filter is suggested. this background estimate is then used to recast the segmentation problem as one of outlier detection, and the result of segmentation is used to modify the filter update. Ways of making the technique computationally benign are discussed. the technique is used to analyse a simulated image sequence, and the performance is compared to that of a single-frame back-round-estimation technique. the feasibility of target segmentation via background tracking is thus demonstrated.

关键词： Image segmentation Filtering (signal processing) Target detection Matrices Cameras Image filtering Digital filtering Electronic filtering Optical filters Image analysis

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Detection and localization of multiple unresolved extended objects via monopulse radar signal processing

Detection and localization of multiple unresolved extended o...

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17th conference on signal and data processing of small targets

作者： Zhang, X Willett, P Bax-Shalom, Y Univ Connecticut Dept Elect & Comp Engn Storrs CT 06269 USA

ISBN: (纸本)0819459186

With high resolution radars, realistic objects should be considered as extended rather than point targets. If several closely-spaced targets fall within the same radar beam and between adjacent matched filter samples in range, the full monopulse information from all of these samples can and should be used for estimation, both of angle and of range (with the range to sub-bin accuracy). To detect and localize multiple unresolved extended targets, we establish a model for monopulse radar returns from extended objects, and use a maximum likelihood estimator to localize the targets. Rissanen's minimum description length (MDL) will be used to decide the number of existing extended objects. We compare the new extended target monopulse processing scheme with previously developed point target monopulse techniques to show the improvement in terms of the estimation of target locations, the detection of the number of existing targets, and the tracking performance with a multiple hypothesis tracker (MHT) using the output from the proposed extended target monopulse processor.

关键词： monopulse radar extended target unresolved target tracking

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Robust scale invariant small target detection using the Laplacian scale-space theory

Robust scale invariant small target detection using the Lapl...

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20th conference on signal and data processing of small targets

作者： Kim, Sungho Yang, Yukyung Lee, Joohyoung Park, Yongchan Agcy Defense Dev Taejon 305600 South Korea

ISBN: (纸本)9780819471604

this paper presents a new small target detection method using scale invariant feature. Detecting small targets whose sizes are varying is very important to automatic target detection in infrared search and track (IRST). the conventional spatial filtering methods with fixed sized kernel show limited target detection performance for incoming targets. the scale invariant target detection can be defined as searching for maxima in the 3D (x, y, and scale) representation of an image with the Laplacian function. the scale invariant feature can detect different sizes of targets robustly. Experimental results with real FUR images show higher detection rate and lower false alarm rate than conventional methods. Furthermore, the proposed method shows very low false alarms in scan-based IR images than conventional filters.

关键词： small target robust detection varying size scale invariant scale-space

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A bio-electromechanical imaging technique with combined electrical impedance and ultrasound tomography

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PHYSIOLOGICAL MEASUREMENT 2008年第6期29卷 S63-S75页

作者： Steiner, G. Soleimani, M. Watzenig, D. Graz Univ Technol Inst Elect Measurement & Measurement Signal Proc A-8010 Graz Austria Univ Bath Dept Elect & Elect Engn Bath BA2 7AY Avon England

Electrical impedance tomography (EIT) seeks to image the electrical conductivity of an object using electrical impedance measurement data at its periphery. Ultrasound reflection tomography (URT) is an imaging modality that is able to generate images of mechanical properties of the object in terms of acoustic impedance changes. Both URT and EIT have the potential to be used in various medical applications. In this paper we focus on breast tumour detection. Both URT and EIT belong to soft field tomography and suffer from the small amounts of available data and the inherently ill-posed nature of the inverse problems. these facts result in limited achievable reconstruction accuracy and resolution. A dual bio-electromechanical tomography system using ultrasound and electrical tomography is proposed in this paper to improve the detection of the small-size tumour. data fusion techniques are implemented to combine the EIT/URT data. Based on simulations, we demonstrate the improvement of detection of small size anomalies and improved depth detection compared to single modality soft field tomography.

关键词： breast imaging dual modality tomography electrical impedance tomography sensor fusion ultrasound tomography

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small object detection via fast discrete Curvelet transform

Small object detection via fast discrete Curvelet transform

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25th SPIE conference on signal and data processing of small targets

作者： Valdez, Hector A. Lu, thomas T. Chao, Tien-Hsin Calif State Univ Long Beach Long Beach CA 90840 USA CALTECH Jet Prop Lab 4800 Oak Grove Dr Pasadena CA 91125 USA

ISBN: (纸本)9780819497079

this paper describes the Fast Discrete Curvelet Transform (FDCT) which is integrated into an automated object detection framework capable of fast image processing for the purpose of tracking multiple objects of interest. the distinguishing difference between FDCT and other transforms is that the Curvelet coefficients have three beneficial parameters, which define scale, orientation, and spatial locations. We utilize these parameters to efficiently detect relatively small objects in a variety of image and video data sets. We have implemented the FDCT in a multi-stage automatic target recognition (ATR) architecture. the results of the current algorithm yield a highly sensitive detection of small targets in noisy backgrounds.

关键词： ATR Curvelet object detection ROI sparse representation targeting

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An Examination of the Application of Space Time Adaptive processing for the Detection of Maritime Surface targets from High Altitude Airborne Platforms

An Examination of the Application of Space Time Adaptive Pro...

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25th SPIE conference on signal and data processing of small targets

作者： McDonald, Michael Cerutti-Maori, Delphine Def R&D Canada 3701 Carling Ave Ottawa ON Canada Fraunhofer FHR D-53343 Wachtberg Germany

ISBN: (纸本)9780819497079

An examination of the application of Space Time Adaptive processing (STAP) techniques to real, multi-channel, medium grazing angle, radar sea clutter data is undertaken and the detection performance is quantified against simulated moving maritime surface targets. the application of sub-optimal STAP approaches to the maritime radar detection problem is shown to be complicated by non-stationarity of sea clutter and rapid variations of the sea clutter spectrum due to transient wave activity. Observed performance gains from maritime STAP are much more limited than those observed for Ground Moving Target Indication (GMTI) due to the inherent spectral width of sea clutter and the slow Doppler velocities of maritime targets. three sub-optimal STAP processing architectures are examined and PRI-Staggered Post-Doppler is shown to provide consistently superior detection performance for the data set in question.

关键词： Maritime surveillance STAP Radar GMTI

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A Fuzzy Based Gaussian Weighted Moving Windowing for Denoising Electrocardiogram (ECG) signals 13th

A Fuzzy Based Gaussian Weighted Moving Windowing for Denoisi...

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13th International conference on Application of Fuzzy Systems and Soft Computing (ICAFS)

作者： Kavalcioglu, Cemal Bilgehan, Bulent Near East Univ Dept Elect & Elect Engn Near East BlvdPOB 99138Mersin 10 Nicosia Trnc Turkey

ISBN: (纸本)9783030041649

the electrocardiogram is a graphical record of the biological signal that is thought to be susceptible to electrical activity of the heart and utilized in order to clinical diagnosis. Electrocardiogram signal is very responsive in nature, and even if there is small noise mixed with the original signal, assorted characteristics of signal change. ECG signal voltage level is as low as 0.5 to 5 mV and is sensitive to artifacts larger than this. Human electrocardiogram signal range frequency ingredients from 0.05 Hz to 100 Hz and are related to noise, muscle movements, network current, and ambient electromagnetic interference. Electrocardiogram is a very significant sign detects abnormal heart rhythms and examines cause of chest pain and widely utilized in cardiology. Most digital signals are infinitely large or too large to be manipulated as a whole. Because statistical calculations require that all points be present for analysis, it is difficult to statistically analyze sufficiently large signals. To avoid these problems, engineers characteristically analyze small subsets of the aggregate data with an operation named windowing. Fuzzy logic is a mathematical logic that attempts to solve problems with a clear, uncertain data spectrum that makes it possible to obtain a series of correct results. this manuscript suggests denoising method Gaussian Weighted Moving Windowing for denoising Electrocardiogram signals to remove random noise. this study is interpreted with the actual data set and confirmed according to Peak signal to noise ratio.

关键词： Electrocardiogram Windowing Gaussian weighted moving windowing Denoising ECG signal processing Fast fourier transform Fuzzy logic

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