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

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Equivalence classes of future paths for sensor allocation and threat analysis

Equivalence classes of future paths for sensor allocation an...

引用

17th conference on signal and data processing of small targets

作者： Svenson, P Swedish Def Res Agcy Div Command & Control Syst Dept Data & Informat Fus SE-16490 Stockholm Sweden

ISBN: (纸本)0819459186

Sensor allocation and threat analysis are difficult fusion problem that can sometimes be approximately solved using simulations of the future movement of adversary units. In addition to requiring, detailed motion models, such simulation also requires large amounts of computational resources, since a large number of possibilities must be examined. In this paper, we extend our previously introduced framework for doing such simulations more efficiently. the framework is based on defining equivalence classes of future paths of a set of units. In the simplest case, two paths are considered equivalent if they give rise to the same set of observations. For sensor management, each considered sensor plan thus entails an equivalence relation on the set of future paths. this can be used to significantly reduce the number of "alternative futures" that need to be considered for the simulation. For threat analysis, the equivalence relation can instead be based on the perceived threat against own units. We describe how the equivalence classes induced by such relations could be used to improve the visualization of threat analysis systems. User interaction can also be used to refine the equivalence classes;we argue that such interaction will be essential for international operations where is it difficult to define actors and targets.

关键词： sensor management resource allocation threat analysis

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Fusion of uncertain combat identity declarations and implication rules using the belief function theory

Fusion of uncertain combat identity declarations and implica...

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17th conference on signal and data processing of small targets

作者： Ristic, B Smets, P Def Sci & Technol Org ISRD Labs 200 Edinburgh SA 5111 Australia

ISBN: (纸本)0819459186

Surveillance systems typically perform target identification by fusing target ID declarations supplied by individual sensors with a prior knowledge-base. Target ID declarations are usually uncertain in the sense that: (1) their associated confidence factor is less than unity, (2) they are non-specific (the true hypothesis belongs to a subset A of the universe 9). Prior knowledge is typically represented by a set of possibly uncertain implication rules. An example of such a rule is: if the target is Boeing 737 than it is neutral or friendly with probability 0.8. the uncertainty auain manifests itself here in two ways: the rule holds only with a certain probability (typically less than 1.0) and the rule is non-specific (neutral or friendly). the paper describes how the fusion of ID declarations and the implication rules can be handled elegantly within the framework of the belief function theory as understood by the transferable belief model (TBM). Two illustrative examples are worked out in details in order to clarify the theory.

关键词： data fusion target identification belief function evidential theory transferrable belief model implication rules

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Bayesian tracking with Dempster-Shafer measurements

Bayesian tracking with Dempster-Shafer measurements

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17th conference on signal and data processing of small targets

作者： Mahler, R Lockheed Martin MS2 Tact Syst Eagan MN USA

ISBN: (纸本)0819459186

the theory and practice of single-sensor, single-target tracking is well understood when measurement uncertainties are due entirely to randomness. In this case the Bayes filter and its special cases and approximations, such as the Kalman filter, constitute the foundations of tracking. However, the measurement uncertainties in many observation-types (features, natural-language reports, etc.) can axise from ignorance as well as randomness. Approaches such as the Dempster-Shafer (DS) theory claim to address such information but continue to be controversial, especially in tracking. In other papers this year we have shown that this can be attributed to a lack of formal physical modeling techniques. If familiar measurement models axe extended in a natural way, measurement fusion using DS combination can be subsumed within the Bayesian theory. In this paper we apply these results to introduce the "evidential filter," a special case of the Bayes filter applicable whenever measurement uncertainty can be modeled in DS form. We derive closed-form formulas for the evidential filter;and show that data-update using Dempster's combination is a special case of Bayes' rule. We also briefly show how to incorporate the evidential filter into multitarget tracking techniques.

关键词： Filtering (signal processing) Fuzzy logic Electronic filtering Digital filtering Linear filtering Sensors Motion measurement Electroactive polymers Mathematical modeling Motion models

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A novel 2-D DOA estimation algorithm with superior resolution and reduced sidelobes - art. no. 591302

A novel 2-D DOA estimation algorithm with superior resolutio...

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17th conference on signal and data processing of small targets

作者： Marino, CS Chaua, PM Univ Calif San Diego Dept Elect & Comp Engn La Jolla CA 92093 USA

ISBN: (纸本)0819459186

We present a 2-D Direction of arrival algorithm whose resolution is superior to that of the subspace class of algorithms and sidelobes are reduced compared to most algorithms. the algorithm is based on the 2-D AR Power Spectral Density (2-D ARPSD) applied to a uniformly spaced data set (space-time) which transforms the space-time data to spatial frequency (wavenumber, which is a function of the direction of arrival) and temporal frequency in a high resolution context. this is done by modeling the sensor array data with a 2-D AR model. the 2-D AR parameters are then used in a specialized form of a 2-D FFT to create an enhanced wavenumber-frequency image. A wavenumber vector for a specific narrowband temporal frequency is extracted and compared to other high resolution algorithm such as MUSIC. Our results exhibit superior performance in low SNR and short sample sized scenarios and when mismatch occurs in the subspace techniques. Our technique also exhibits reduced sidelobes as compared with traditional methods.

关键词： Autoregressive models data modeling signal to noise ratio Sensors Interference (communication) Image enhancement Temporal resolution Antennas Computer simulations Spectral resolution

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Tracking and classification with attribute data from multiple legacy sensors - art. no. 591319

Tracking and classification with attribute data from multipl...

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17th conference on signal and data processing of small targets

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

ISBN: (纸本)0819459186

An obvious use for feature and attribute data is for classification and in combat identification. the term classification is used broadly here to include discrimination, detection, target typing, identification, and pattern recognition. An additional use is in the data (or track) association process to reduce the misassociations, often called feature aided tracking. Previous papers discussed the integration of features and attributes into target track processing in addition to their use in multiple target classification. the distinction is made between feature and attribute data because they are processed differently. the term features applies to random variables from continuous sample space and attributes applies to random variable data from discrete sample space. the primary concern of this paper is to address processing of attributes with data from legacy sensors. For example, in fusion of sensor data from distributed sensors, a sensor might distribute the likelihood of the most likely target class (or attribute property) and no information on the other possibilities. In another example, a sensor might distribute the likelihood that the target is any one of a number of target classes, a subset of all the target classes, rather than indicating one specific target class. Both attribute aided tracking and (post tracker) target classification are addressed for these examples of incomplete data from legacy sensors. the purpose of this paper is to show the feasibility of simple approaches to dealing with data from some legacy sensors.

关键词： Multiple target tracking feature aided tracking features attributes categorical features multiple models Bayesian methods Kalman filter.

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Imaging of subsurface targets using a 3D quadtree algorithm

Imaging of subsurface targets using a 3D quadtree algorithm

引用

IEEE 13th signal processing and Communications Applications conference, SIU 2005

作者： Gürbüz, Ali Cafer McClellan, James H. Scott Jr., Waymond R. Elektrik ve Bilgisayar Mühendisliǧi Bölümü Georgia Insitute of Technology Atlanta

ISBN: (纸本)0780392396

the imaging of subsurface targets using Ground Penetrating Radar (GPR) is becoming an increasingly important area of research. Conventional image formation techniques expend large amounts of computational resources on fully resolving a region, even regions of clutter. However, by using multi-resolution techniques - e.g, quadtree algorithms - potential targets and clutter can be discriminated in a computationally efficient way. Prior work has focused on the development of 2D quadtree algorithms for surface targets. For mine detection, target depth adds another dimension;thus, we have developed a 3D quadtree algorithm, and applied a multi-stage detector that uses the energy change between quadtree stages to discriminate target and clutter regions. this algorithm is then tested on computer-generated data, as well as experimental data collected from a model mine field. Results show that target location information can be obtained even under near field and small aperture conditions. © 2005 IEEE.

关键词： Imaging techniques

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Performance analysis of underwater hydrophone arrays in tracking manoeuvring sea-surface targets - art. no. 591314

Performance analysis of underwater hydrophone arrays in trac...

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17th conference on signal and data processing of small targets

作者： Hernandez, ML Goddard, N QinetiQ Ltd Malvern Technol Ctr CSIP Malvern WR14 3PS Worcs England

ISBN: (纸本)0819459186

In this paper, we assess the capability of underwater hydrophone (UH) arrays to locate and track manoeuvring targets. A UH array is a horizontal line array of omnidirectional pressure sensors that is deployed on the seabed. the measurements at each UH array are then affected by two idiosyncrasies, termed "source direction ambiguity" and "coning error". In this paper, the posterior Cramer-Rao lower bound (PCRLB) is used as the measure of system performance, providing a bound on the optimal achievable accuracy of target state estimation. We demonstrate the impact of the measurement idiosyncrasies on the PCRLB, with the bound shown to be greater (poorer performance) than when using standard bearings-only sensors. We also include clutter (i.e. we allow each measurement to be either target generated or a false positive), as well as both state-dependent measurement errors and a state-dependent probability of detection. Building on previous work, we show that the measurement origin uncertainty can again be expressed as an information reduction factor (IRF), with this IRF now shown to be a function of both the target range and orientation in relation to each UH array. We consider simulated scenarios that contain features characteristic of recent sea trials conducted by QinetiQ Ltd. the two key features of the trial scenarios is that we have very sparse prior knowledge, and each target has the potential to perform a series of manoeuvres. We use a recent PCRLB formulation for tracking manoeuvring targets that approximates the potentially multi-modal target distribution using a best-fitting Gaussian distribution. We present simulation results for multi-sensor scenarios, demonstrating that this is indeed a difficult tracking problem. Tracking is particularly difficult when the target crosses the line of the UH arrays, making triangulation difficult;and when the target is in the "end-fire" of at least one UH array. It is also difficult to detect and triangulate distant targets.

关键词： posterior cramer-rao lower bound underwater hydrophone Arrays manoeuvring target tracking information reduction factor best-fitting Gaussian approximation

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Multitarget tracking and monopulse signal processing for spawning targets

Multitarget tracking and monopulse signal processing for spa...

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16th conference on signal and data processing of small targets

作者： Willett, P Blair, WD Ogle, T Univ Connecticut Storrs CT USA

ISBN: (纸本)081945351X

A monopulse radar is able to derive accurate angular measurements via intelligent processing of its sum and difference channel returns. Recently there have emerged techniques for angular estimation of several unresolved targets. meaning targets that are. in principle, merged within the same radar beam, can be extracted separately. the key is the joint exploitation of information in several range bins. Here we show the performance of this approach in a high-fidelity simulation: we observe considerable improvement in track RMSE, but little corresponding, gain in track completeness. Coupled with a hidden Markov model on target number, however, the performance is impressive.

关键词： radar target tracking radar signal processing resolution

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Detection of small target in IR image sequences using VSLMS

Detection of small target in IR image sequences using VSLMS

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16th conference on signal and data processing of small targets

作者： Ng, LN Ronda, V Lim, ET Nanyang Technol Univ Sch Elect & Elect Singapore Singapore

ISBN: (纸本)081945351X

A Vertical-Strip Least Mean Squared (VSLMS) algorithm is proposed to enhance the detection of small moving targets in IR image sequences. this algorithm is an improvement over the Two-Dimensional LMS (TDLMS), which is designed to detect small targets within highly correlated background of static images. this paper focuses on processing IR image sequences with different background features with layers of sky, sea and land clutter. the VSLMS uses multiple LMS modules and a different scanning method to process individual lines in the IR image sequences. Simulation results show successful enhancement of very small targets in an IR mage sequence.

关键词： VSLMS IR image sequences TDLMS

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Fast mutual exclusion

Fast mutual exclusion

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16th conference on signal and data processing of small targets

作者： Maskell, S Briers, M Wright, R QinetiQ Ltd Malvern Technol Ctr Malvern Worcs England

ISBN: (纸本)081945351X

A method is presented that circumvents the combinatorial explosion often assumed to exist when summing probabilities of joint association events in a multiple target tracking context. the approach involves no approximations in the summation and while the number of joint events grows exponentially with the number of targets, the computational complexity of the approach is substantially less than exponential. Multiple target tracking algorithms that use this summation include mutual exclusion(11,21) in a particle filtering context and the Joint Probabilistic data Association Filter,(7) a Kalman Filter based algorithm. the perceived computational expense associated with this combinatorial explosion has meant that such algorithms have been restricted to applications involving only a handful of targets. the approach presented here makes it possible to use such algorithms with a large number of targets.

关键词： Detection and tracking algorithms Filtering (signal processing) Electronic filtering Particle filters Particles

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