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检索条件"任意字段=18th Conference on Signal and Data Processing of Small Targets"

共 390 条记录，以下是51-60 订阅

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Method for reticon signal processing in the Lower Latitude Meridian Circle (LLMC)

Method for reticon signal processing in the Lower Latitude M...

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13th conference on signal and data processing of small targets

作者： Li, BH Yang, L Mao, W Tie, QX Wang, XB Zhang, ZS Chinese Acad Sci Yunnan Observ Kunming Peoples R China

ISBN: (纸本)0819441872

the functions and characteristics of the 1(st) to 9(th) Reticon signals used to measure positions of reticle/slit images in the LLMC are described in this paper. According to their characteristics, we present a new method to process these Reticon signals, which consists of a filtering algorithm and a centering algorithm. the filtering algorithm is developed to process the 5(th) to 9(th) Reticon signals, because in these signals there are obvious disturbance components caused by the backaround light in the microscopes. An auto-estimating technique is developed to estimate and eliminate the disturbance signal of the background light by a piecewise-linear fitting. the centering algorithm is used to determine the positions of all the reticle/slit images in 3 steps. the first is to search all the wave crests and troughs of a Reticon signal, the next is to determine a threshold for each wave and then to center the wave by a modified moment method so as to get the position of the reticle/slit image, and the last step is to average all the position data of the waves in a Reticon signal to get an integrate position data of a group of reticles/slits in the corresponding reading microscope, the technique of implementation of the method in C++ programming language is also described in the paper.

关键词： signal processing filtering centering Reticon LLMC

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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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SEMI-AUTOMATIC 3-D SEGMENTATION OF COMPUTED TOMOGRAPHIC IMAGERY BY ITERATIVE GRADIENT-DRIVEN VOLUME GROWING

SEMI-AUTOMATIC 3-D SEGMENTATION OF COMPUTED TOMOGRAPHIC IMAG...

引用

18th IEEE International conference on Image processing (ICIP)

作者： Vantaram, Sreenath Rao Saber, Eli Dianat, Sohail Hu, Yang Abhyankar, Vishwas Rochester Inst Technol Chester F Carlson Ctr Imaging Sci Rochester NY 14623 USA Rochester Inst Technol Dept Elect & Microelect Engn Rochester NY 14623 USA Data Phys Res Incorp San Ramon CA 94583 USA

ISBN: (纸本)9781457713033

We propose a novel gradient driven methodology for three dimensional (3-D) segmentation of Computed Tomographic (CT) imagery. Our approach begins interactively where-in a user marks a set of voxels within the cross-section of a Sub-Volume Of Interest (SVOI), using a single slice of the CT volume. Subsequently, a 3-D gradient detection scheme is utilized to determine the radiodensity variations across the volume. the resultant gradient information is employed in an iterative volume growing procedure, which is initiated at voxels with small gradient magnitudes adjoining the user-selected voxels and culminates at voxels with large gradient magnitudes, to arrive at the final 3-D segmentation result of the SVOI. the aforementioned method was tested on multiple studies and the results show favorable performance against a state-of-the-art technique.

关键词： Volumetric segmentation 3-D gradient detection volume growing

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GMTI-tracking and information fusion for ground surveillance

GMTI-tracking and information fusion for ground surveillance

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13th conference on signal and data processing of small targets

作者： Koch, WG FKIE FGAN D-53343 Wachtberg Germany

ISBN: (纸本)0819441872

the aim of ground surveillance with airborne GMTI radar is the near real-time production of a dynamic ground picture. Since the sensors often record merely certain aspects of the situation of interest, information fusion is of particular importance. In addition, even after platform motion compensation by signal processing techniques (STAP), ground moving targets can well be masked by the clutter notch of the sensor. this physical phenomenon directly results from the low-DOPPLER characteristics of the targets and causes interfering fading effects that seriously affect the tracking performance/continuity. In this context a GMTI sensor model provides significant performance improvements being relevant also to sensor data fusion. the Minimum Detectable Velocity (MDV) proves to be an important sensor parameter explicitly entering into GMTI tracking. In combination with road map information or sensor data fusion the refined model can in particular alleviate the recognition of stopping targets. A numerical example quantitatively illustrates the potential gain by exploiting GMTI-modeling, road-maps, and sensor fusion.

关键词： ground moving targets (GMT) GMTI radar Bayesian target tracking PDA MHT sensor data fusion road map information minimum detectable velocity (MDV) space-time adaptive processing (STAP) doppler blindness

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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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Use of joint data association probabilities for covariance consistency

Use of joint data association probabilities for covariance c...

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13th conference on signal and data processing of small targets

作者： Blair, WD Brown, GC Georgia Inst Technol Georgia Tech Res Inst Atlanta GA 30332 USA

ISBN: (纸本)0819441872

Covariance consistency is a critical element of a robust target tracking system. Target maneuvers and measurement origin uncertainty pose significant challenges to a tracking algorithm achieving covariance consistency. the Interacting Multiple Model (IMM) estimator is a nearly consistent estimator for tracking maneuvering targets. While the Probabilistic data Association Filter (PDAF) achieves covariance, consistency for a single target in presence of false alarms, achieving covariance consistency while tracking multiple closely-spaced targets is an open Issue. When using an unique assignment technique for associating measurements-to-tracks, the measurements are typically processed with the track filter as if the measurement-to-track association probabilities are unity for each measurement-track pair. this processing of the measurements results in poor covariance consistency for closely-spaced targets. In this paper, the use of approximate association probabilities for each measurement-to-track pair is proposed for the unique assignments and included in the track filter processing of the measurement to enhance the covariance consistency for closely-spaced targets.

关键词： tracking data association radar systems

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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 16-channel readout chip - A new sparse data readout architecture 18

A 16-channel readout chip - A new sparse data readout archit...

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18th European Solid-State Circuits conference, ESSCIRC 1992

作者： Murray, R. Lovell, M. Didcot Oxfordshire United Kingdom

ISBN: (纸本)8798423207

this paper describes a new architecture for performing data compression on a large matrix of parallel digital inputs, only a small proportion of which carries a logical T. the system assigns a unique address to each of the active inputs (suppressing the inactive ones) and feeds them serially onto a data bus. the architecture is implemented using an array of CMOS digital signal processing ASICs, which have been designed at R.A.L, England and tested at C.E.R.N. in Geneva. © 1992 European Solid-State Circuits conference.

关键词： Digital signal processing

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