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Simulation of signal and data processing for a pair of GEO IR sensors

Simulation of signal and data processing for a pair of GEO I...

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19th conference on signal and data processing of small targets

作者： Keil, Karl-Heinz Hupfer, Werner EADS Astrium GmbH Bremen Germany

ISBN: (纸本)9780819468475

this paper describes experiences and results from developing a basic signal and data processing simulation for a pair of GEO IR sensors observing the boost phase of theater Ballistic Missiles (TBM). the goal of such a system is the detection of launched TBM, also against a cloud background, and the tracking from cloud break ideally up to boost-end. Two GEO satellites are used for stereo view of one and the same non-global limited Field-of-Regard (FOR). they are positioned in such a way that both cover the FOR and provide a sufficient triangulation baseline. signal processing is applied for each of both passive IR sensors in order to detect and track the TBM on the focal plane. the applied approach can be summarized under the term 'velocity filtering'. data processing operates on the 2-D signal processing input from both IR sensors, i.e. azimuth and elevation line-of-sight (LOS) angles as well as their rates. the goal is to provide 3-D tracks of the targets, which can be used to cue early warning or fire control radars. the underlying simulation model constitutes a prototype and vehicle for further research. Nevertheless, even in its current stage it provides a first tool for the analysis and evaluation of corresponding sensor design concepts.

关键词： signal processing data processing Satellites Filtering (signal processing) Digital filtering Sensors Clouds Infrared sensors Target detection Optical filters

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Target classification with data from multiple sensors

Target classification with data from multiple sensors

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14th conference on signal and data processing of small targets

作者： Drummond, OE CyberRnD Inc Culver City CA 90230 USA

ISBN: (纸本)0819444782

the methods used in the classification of multiple small targets can be very different from the methods commonly used in traditional pattern recognition. First, there may be characteristics of the features for. each target class that can permit simpler computations than other features. In addition, in classifying targets, the target tracks are updated as new data becomes available and hence there can be a sequence of feature measurements that are available for the target classification process. In addition, with multiple targets, the a priori information may be in a form that make the classification processing for one target dependent on the classification processing of other targets. these aspects of target classification that make that processing different from traditional pattern recognition are the concern of this paper. To limit the length of the paper, the scope is restricted to classification tasks that allow the linear-Gaussian assumption to be used. Also, the data used in the classification process is restricted to features, i.e., no attributes, and the assumption is the tracker does not employ feature-aided tracking. While these assumptions simplify the discussion, the methods used could be modified to permit classification of a broad scope of classification tasks.

关键词： multiple target tracking features target typing detection classification recognition identification and discrimination automatic target recognition (ATR) multiple models Bayesian methods and Kalman filter

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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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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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Comparison of adaptive array processing schemes for land mine detection using hyperspectral imagery - art. no. 591301

Comparison of adaptive array processing schemes for land min...

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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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Alternative architectures for IMM tracking of maneuvering aircraft

Alternative architectures for IMM tracking of maneuvering ai...

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14th conference on signal and data processing of small targets

作者： Hutchins, RG Wilson, D Allred, LK Duren, R USN Postgrad Sch Monterey CA USA

ISBN: (纸本)0819444782

this paper presents the results of a study of tracking algorithms for maneuvering targets. the design focuses on alternative algorithms to track two-dimensional targets during maneuvers. the algorithms explored include a standard Kalman algorithm, an extended Kalman algorithm in which the target turn rate is an additional state variable, an interactive multiple model (IMM) algorithm consisting of two models with varying plant noise, a three-model IMM specifying three distinct target turn rates, and a constant gain alpha-beta filter. the IMM trackers tended to work the best in this study, with the three-model IMM performing the best overall.

关键词： target tracking maneuvering targets interactive multiple models

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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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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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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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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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