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检索条件"任意字段=Conference on Signal and Data Processing of Small Targets 1999"

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Multifocal matrix method of image forming objects at higher-than-Rayleigh resolution and determining their geometric and dynamic parameters

Multifocal matrix method of image forming objects at higher-...

引用

conference on signal and data processing of small targets 1997

作者： Mandrosov, VI Institute of Physics and Technology (Russia)

ISBN: (纸本)0819425850

A multifocal matrix method for super Rayleigh resolution imaging and determining geometric and dynamic parameters of objects is developed and studied. The key element of the method is a multifocal matrix consists of focusing elements. The coherent light scattered by an object is focused by these elements and focused fields are detected at elements focused. The results of detection are used for determining the angular coordinates, amplitudes and phases of light fields scattered by different parts of the object surface. If the object under investigation consists of closely spaced small targets that cannot be resolved using the Rayleigh criterion, the method provides a useful tool for determining the angular coordinates, velocity, scattering coefficient and the distance of each target. The effect of the additive noise of focusing detector elements on the angular resolution of the method is analysed. The method provides two ways of obtaining information about small targets. The first allows the building of their two-dimensional images, the other is for determining their overall dimensions, rotational speeds, parameters of surface roughness.

关键词： image forming resolution closely spaced small targets processing extended object processing

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Classical and neural solutions for plot-to-track association

Classical and neural solutions for plot-to-track association

引用

conference on signal and data processing of small targets 1997

作者： Winter, M Schmidlin, V Favier, G Univ. of Nice-Sophia Antipolis (France) Univ. of Nice-Sophia Antipolis and Systelia Technologies (France)

ISBN: (纸本)0819425850

This paper presents and compares two alternative classes of solutions to the plot-to-track association problem. The first class of solutions relies on classical approaches of signal processing, principally based on the Bayes theory, that is to say the Nearest-Neighbor Filter, the Probabilistic data Association Filter and the Joint Probabilistic data Association Filter. The data association problem can be reduced to a combinatorial optimization problem, for which the time needed to obtain the exact solution grows drastically with the problem size. This is the reason why, in most cases, we do not look for the best solution, but rather for a good solution, reachable in a reasonable computation time. Consequently, neural networks are an interesting alternative to classical solutions. We first review several neural models: Hopfield networks, Boltzmann machine, mean field approximation networks and our approach derived from the Hopfield model. Then we present some simulation results that enable to compare the various techniques for a general assignment problem and for the multitarget tracking problem.

关键词： Electronic filtering Filtering (signal processing) Neural networks signal processing

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Multi-sensor data fusion method to discern point targets

Multi-sensor data fusion method to discern point targets

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conference on signal and data processing of small targets 1997

作者： Li, H An, W Xu, H Sun, ZK National Univ. of Defense Technology (China)

ISBN: (纸本)0819425850

Two different vehicles which have the same shapes and sizes fly together in upper space at the same velocity. The vehicles are so far away from the sensors that the acquired images are point targets. No shape information can be gotten. These two vehicles fly together and no motion characteristics may be used. Therefore the infrared (IR) radiation characteristics of them are important for discerning these two vehicles. In this paper, three ground-based IR sensors are used to get the TR radiation spectrum of the point targets, and twelve IR characteristics are selected for recognizing them. First, a BP network is used to recognize the point targets at each base. Then a Subjective Bayesian Method is adopted to fuse the recognized results given by BP networks on three bases at the same time. And the result given by Bayesian is fused by D-S Evidence Theory with the result at next time till the belief function is more than threshold. The emulation shows that the last outputs is satisfactory.

关键词： multi-sensor data fusion neural networks subjective Bayesian method evidence theory point targets recognition

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Random sets in data fusion problems

Random sets in data fusion problems

引用

conference on signal and data processing of small targets 1997

作者： Mori, S Raytheon TI Systems (United States)

ISBN: (纸本)0819425850

A general theory of multi-object state-estimation problems, also known as multi-target tracking problems, is presented, using explicit random-set formalism. Probability density functions of random sets, as well as Choquet's capacity functionals, are used to represent random sets, in pursuit of the possibility of such a theory becoming a theoretical foundation of data fusion theory. The theoretical and algorithmic developments over the past three decades in this area are also re-examined in the light of this new formalism, as well as the recent development of correlation-free algorithms that utilize random-set formalism explicitly.

关键词： data fusion multiple-object state-estimation multi-target multi-sensor tracking random sets point processes Choquet's capacity functional assignment problems

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Target tracking with retrodicted discrete probabilities

Target tracking with retrodicted discrete probabilities

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conference on signal and data processing of small targets 1997

作者： Drummond, OE Independent Consulting Engineer (United States)

ISBN: (纸本)0819425850

The concept of retrodiction of discrete probabilities is exploited in this paper to provide alternative data association algorithms for tracking multiple targets with a single or multiple sensors. These algorithms employ multiple frames of data in the data association processing. The concept of retrodiction is also applied to the task of multiple model filtering. Alternative optimization criteria are also exploited to provide alternative association approaches and each approach is expected to exhibit different estimation error characteristics. These additonal association approaches provide wider selction to better tailor the tracking algorithms to a specific application. These approaches offer improved performance over single-frame association tracking approaches. This improved performance is obtained, however, at the expense of increased processing load. A number of different approaches are described that employ multiple-frame data association. Similarly, a number of different approaches are also described that employ a moving window of multiple measurements for multiple model filtering. With these algorithms, design parameters can be selected to adjust performance to suit a specific application.

关键词： target tracking retrodiction multiple sensor tracking multiple target tracking most probable hypothesis data association sensor fusion composite decisions multiple hypotheses multiple model filtering Bayesian methods Kalman filter composite estimation

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data association probability and measurement density function of tracking in clutter with strongest neighbor measurements

Data association probability and measurement density functio...

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conference on signal and data processing of small targets 1997

作者： Li, XR Univ. of New Orleans (United States)

ISBN: (纸本)0819425850

When tracking a target in clutter, a measurement may have originated from either the target, clutter, or some other source. The measurement with the strongest intensity (amplitude) in the neighborhood of the predicted target measurement is known as the ''strongest neighbor'' (SN) measurement. A simple and commonly used method for tracking in clutter is the so-called Strongest Neighbor Filter (SNF), which uses the SN measurement at each time as if it were the true one. This paper presents analytic results, along with discussions, for the SN measurement, including the a priori and a posteriori probabilities of data association events and the conditional probability density functions. These results provide theoretical foundation for performance prediction and development of improved tracking filters.

关键词： target tracking strongest neighbor filter theoretical analysis

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Track-Before-Detect implementation and tests results

Track-Before-Detect implementation and tests results

引用

conference on signal and data processing of small targets 1997

作者： Alon, Y Johnson, DD Mallean, GH Erickson, FW Litton Data Systems Agoura Hills CA United States

ISBN: (纸本)0819425850

A Track-Before-Detect processor has been developed by Litton data Systems Division (DSD), Agoura Hills, CA and implemented in hardware. Its objective was to enhance radar and IR dim target detection in adverse conditions. The unit has been integrated with an operational Radar system and tested in real time scenarios. This paper describes the processor target detection performance in sea clutter, weather and noise. In specific it addresses the issue of maritime radar detection performance as were observed during sea trials data collection tests. Performance in sea clutter for Infra Red (IR) sensor is also provided.

关键词： Track Before Detect Dim Target Detection Sea clutter Decorrelation Weather Clutter Rejection

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Hot starts for track maintenance in multisensor-multitarget tracking

Hot starts for track maintenance in multisensor-multitarget ...

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conference on signal and data processing of small targets 1997

作者： Poore, AB Colorado State Univ. (United States)

ISBN: (纸本)0819425850

Large classes of data association problems in multiple hypothesis tracking applications involving multiple and single sensor systems can be formulated as multidimensional assignment problems, which are then fundamental in both track initiation and maintenance. In particular, track maintenance uses an N-frame moving window over the scans of data from multiple sensors giving rise to the repeated solution of (N + 1)-dimensional assignment problems. Due to the complexity of these NP-hard problems and the fact that one must solve these problems to the noise level in the problem, it is most advantageous to take advantage of a previously solved problem over a previous window. This work explores this issue in track maintenance.

关键词： Sensors Computer programming Algorithm development Detection and tracking algorithms Surveillance data fusion Mathematics Patents Scientific research Surveillance systems

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Pipe-lined algorithm and parallel architecture for real-time detection of sparse small objects in images

Pipe-lined algorithm and parallel architecture for real-time...

引用

conference on signal and data processing of small targets 1997

作者： Ito, MR Duong, S McFee, JE Russell, KL Univ. of British Columbia (Canada) Defence Research Establishment Suffield (Canada)

ISBN: (纸本)0819425850

A pipe-lined algorithm and parallel architecture is under development for real time detection of sparse small objects in images. Monochromatic images from an airborne active infrared scanner, images from a low-altitude aircraft-mounted multispectral scanner, and passive infrared imagery obtained from cameras mounted on ground vehicle are the image types intended for the application of this system to the detection of minefields. The paper briefly describes the characteristics of these three different kinds of image sensors and the operating environments. The general image processing system architecture and the functions of each of the components are also presented The feature selection and algorithm adaptations for each of the image classes are described. Preliminary results obtained from an experimental system consisting of a small transputer network and array processors are discussed.

关键词： remote minefield detection pipe-lined algorithm parallel architecture real-time image analysis

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Detection of small targets in clutter modeled as a Gaussian mixture or hidden Markov process

Detection of small targets in clutter modeled as a Gaussian ...

引用

conference on signal and data processing of small targets 1997

作者： Stein, DWJ NCCOSC RDTE DIV 761 San Diego CA 92152 United States

ISBN: (纸本)0819425850

Sea clutter amplitude is often modeled as a compound random variable Z = AX, where A is a positive valued random variable and X has a Rayleigh distribution. The K, class A, and discrete Rayleigh mixture distributions can be derived from these assumptions. Moreover, successive values of A may be correlated. If A is modeled as a finite Markov process, Z is described by a hidden Markov model (HMM). The applicability of Rayleigh mixture and hidden Markov models to RADAR sea clutter is demonstrated empirically Amplitude only and phase coherent detection statistics are derived from these models using locally optimal and likelihood ratio techniques. Robust implementations of the locally optimal processor based on the Rayleigh mixture model have been developed, and empirical ROC curves demonstrate performance improvement of up to 9 dB in comparison with a CFAR detector for small targets in sea clutter. In a test case, the locally optimal hidden Markov detector is then shown to offer an additional 3 dB over the Gaussian mixture detector. Further examples compare the amplitude and phase coherent hidden Markov detectors with CFAR and Doppler processors.

关键词： detection in clutter hidden Markov models Gaussian mixture distributions

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