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检索条件"主题词=Detection and tracking algorithms"

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ROBOT POSITION ESTIMATION USING RANGE AND COMPASS DATA 6

ROBOT POSITION ESTIMATION USING RANGE AND COMPASS DATA

引用

CONF ON MOBILE ROBOTS 6

作者： MALIK, R BENTEFTIFA, B Stevens Institute of Technology (United States)

ISBN: (纸本)081940750X

In this paper, a method for mobile robot positioning using range data is investigated. A ranging sensor is used to collect range data within an environment modeled as a closed polygon, and a compass is available to provide the ranging sensor with direction. The problem of position uncertainty is defined as the existence of multiple position solutions when angle readings are noiseless. When the compass is not ideal, the problem is further complicated by now having imprecise multiple solutions. Both cases are solved by introducing a function defined as the region entropy, which provides us with the ranging angle directions that minimize the uncertainty in position estimation. A least square position estimation method is then proposed. Finally, an example is used to illustrate the technique described above.

关键词： Ranging Mobile robots Sensors Telecommunications Data modeling Environmental sensing Ions detection and tracking algorithms Error analysis Lead

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ESTIMATION OF TARGET SCATTERING CENTERS USING NEURAL NETWORK LEARNING algorithms

ESTIMATION OF TARGET SCATTERING CENTERS USING NEURAL NETWORK...

引用

2ND INTERNATIONAL CONF ON AUTOMATIC OBJECT RECOGNITION

作者： JOUNY, I Lafayette College (United States)

ISBN: (纸本)0819408654

An adaptive neural network learning algorithm is used to estimate the location of radar targets scattering centers. The performance of the implemented spectral estimation scheme depends on learning rate, number of training vectors, and the length of each training vector. The neural network learning spectral estimation algorithms used in this study is an attractive alternative to traditional high resolution spectral estimation schemes because the number of spectral peaks depends not only on a model order assigned a priori, but also on the level of training, learning rate, and convergence. Also, neural networks are adaptive to changes in data, fault tolerant, and may be implemented using analog circuitry. Scattering features extracted using neural networks are used for target classification. The performance of the proposed target recognition scheme is compared with that of nearest neighbor based classifier.

关键词： Neural networks Scattering detection and tracking algorithms Evolutionary algorithms Radar Fourier transforms Target recognition Object recognition Signal to noise ratio Data modeling

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INCORPORATING COLOR AND SPATIOTEMPORAL STEREOVISION TECHNIQUES FOR ROAD FOLLOWING

INCORPORATING COLOR AND SPATIOTEMPORAL STEREOVISION TECHNIQU...

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11TH CONF ON INTELLIGENT ROBOTS AND COMPUTER VISION : algorithms, TECHNIQUES, AND ACTIVE VISION

作者： SUNG, E MYINT, T Nanyang Technological Univ. (Singapore)

ISBN: (纸本)0819410268

This paper proposes a method of implementing stereovision in existing mobile robot perception systems without having to solve the classical stereo correspondence problem. The proposed method makes use of the fact that tracking of features is an easier task than performing stereo correspondence. A two-view motion stereo system is implemented in which the correspondence between two cameras is found by temporal stereo tracking. The algorithm assumes an initial stereo match of homologous features seen in the two cameras but subsequently the algorithm reliably tracks each feature by use of accurate odometric information, and accurate 3-D information can be derived from each matched feature. The derived set of 3-D data (of points, lines, and regions) are then fed to a fast surface reconstruction algorithm for later stage interpretation. The proposed scheme can be added to existing mobile robot road following systems at little added cost.

关键词： Cameras Roads Image segmentation detection and tracking algorithms Robots Calibration Mobile robots Computer vision technology Machine vision Robot vision

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PARAMETRIC STUDY OF THE EFFECT OF VIEWING GEOMETRY ON MONO AND STEREO tracking

PARAMETRIC STUDY OF THE EFFECT OF VIEWING GEOMETRY ON MONO A...

引用

6TH CONF ON ACQUISITION, tracking, AND POINTING

作者： STENGEL, K Nichols Research Corp. (United States)

ISBN: (纸本)081940862X

This study considers a satellite-mounted sensor in a 1000-km circular orbit. The sensor is initially placed north, south, east, or west of a ballistic target, at a variety of initial ranges from 500 km to over 3000 km. The initial angle between the sensor and target velocity vectors is varied, from near zero degrees to roughly 180 deg, in steps of 30 deg. The tracking algorithm used is a standard Kalman filter. The track errors as a function of track time for several track data rates are examined. The error is defined to be the maximum eigenvalue of the covariance matrix. Both the current covariance matrix and the matrix propagated to impact are studied. The study is done for a variety of angular measurement errors, from one microradian to over 100 microradians. The best tracking performance seldom occurs when the target and sensor velocity vectors are crossing, as might be intuitively expected. The track error is very nearly linear with angular error. While increasing the data rate improves tracking performance, doubling the data rate does not improve performance nearly as much as doubling the total track time. Once a good track is obtained, further updates to the track can be very infrequent and the track will still improve steadily with time.

关键词： Sensors Osmium Silicon Filtering (signal processing) detection and tracking algorithms Error analysis Information operations Satellites Automatic tracking Target acquisition

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PRINCIPAL COMPONENT TRAINING OF MULTILAYER PERCEPTRON NEURAL NETWORKS

PRINCIPAL COMPONENT TRAINING OF MULTILAYER PERCEPTRON NEURAL...

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1ST CONF ON SCIENCE OF ARTIFICIAL NEURAL NETWORKS

作者： SUN, GC CHENOWETH, DL Univ. of Louisville (United States)

ISBN: (纸本)0819408751

This paper addresses the problem of training a multi-layer perceptron neural network for use in statistical pattern recognition applications. In particular it suggests a method for training such a network which significantly reduces the number of iterations that usually accompanies the use of the back propagation learning algorithm. The use of principal component analysis is proposed, and an example is given that demonstrates significant improvements in convergence speed as well as the number of hidden layer neurons needed, while maintaining accuracy comparable to that of a conventional perceptron network trained using back propagation. The accuracy obtained by the principal component trained network is also compared to that of a Bayes classifier used as a reference for evaluating accuracies. in addition, a cursory examination of the network performance with uniformly distributed feature classes is included. This work is still of a preliminary nature, but the initial examples we have considered suggest the method has promise for statistical classification applications.

关键词： Neural networks Pattern recognition Principal component analysis Chemical elements Artificial neural networks Neurons detection and tracking algorithms Tolerancing Computer engineering Sun

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CAN MACHINE VISION BE HELPED FROM INSIGHTS INTO HUMAN VISION 3

CAN MACHINE VISION BE HELPED FROM INSIGHTS INTO HUMAN VISION

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CONF ON HUMAN VISION, VISUAL PROCESSING, AND DIGITAL DISPLAY 3

作者： PAVLIDIS, T SUNY/Stony Brook (United States)

ISBN: (纸本)0819408204

Machine vision has exhibited rather slow progress over the last 25 years compared to other areas of Computer Technology and an interesting question is whether more progress will be made by continuing intensively the current approaches in research or instead by searching for new directions. I will present a thesis that more research along some of the prevailing lines will lead to best to marginal advances. For example, current edge detectors are very good at finding step edges. The problem is that their major objective, finding object outlines, is not equivalent to step edge finding. It seems that people find object outlines by a process of simultaneous interpretation and low level processing of the image. Such integration should be contrasted to one of the prevailing models in machine vision which assumes a linear sequence of a few distinct processes from low level to high level vision. (When researches talk about 'interpretation guide segmentation' they usually refer to the labeling of already obtained features using high level models of the scene.) If the levels interact strongly, then optimizing the processing techniques for each level separately (for example edge detection for low level vision) is not going to be fruitful. Since human vision is the reason that we believe that machine vision is even possible, a deeper examination of the human or animal vision recognition process is essential to the further progress of machine vision.

关键词： Machine vision Human vision and color perception Sensors Image processing Image segmentation Visual process modeling detection and tracking algorithms Optical character recognition Visualization Edge detection

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SINGLE LOOK tracking NOISE FOR INTENSITY AND BINARY CENTROIDING algorithms FOR RESOLVED TARGETS AND PERFORMANCE COMPARISON BETWEEN SHARED AND SEPARATE APERTURE ACTIVE tracking

SINGLE LOOK TRACKING NOISE FOR INTENSITY AND BINARY CENTROID...

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4TH CONF ON THE SIGNAL AND DATA PROCESSING OF SMALL TARGETS 1992

作者： BANDERMANN, L KWONG, R Lockheed Missles & Space Co. Inc. (United States)

ISBN: (纸本)0819408638

Expressions are derived for the single look tracking noise (SLTN) for an unthresholded intensity centroid algorithm and a binary centroid with a lower threshold. The SLTN is defined as the rss value of the rms errors due to (1) photoelectron statistics, (2) background in the tracking gate, and (3) non-coincidence of the object boundaries and the focal plane array (FPA) detector pixels. The expressions, eqs. (27) and (28) below, are applied to typical directed energy weapon scenarios where the objects are pulse-illuminated distant, Lambertian targets. We find for both algorithms that the SLTN decreases with increasing illuminator energy to a terminal value set by the boundary mismatch error (3) above, but for a fixed illumination and pixel footprint on the target this error is smaller for the intensity algorithm. For each algorithm, the footprint can be optimized to obtain a minimal SLTN, and in the cases studied the binary SLTN was consistently lower than the intensity SLTN. Furthermore, the dependence on illuminator pulse energy E is approximately 1/(root)E for the intensity, approximately 1/E^2/3 for the binary centroid. Finally, the SLTN is approximately proportional to 1/D(root)(eta) , where D is the collecting aperture and (eta) is the tracker photon efficiency (transmission X quantum). Thus the advantage of a `shared' DEW tracker compared to `separate' is typically a factor 5 or less.

关键词： Binary data detection and tracking algorithms Error analysis Directed energy weapons Data processing Signal processing Fiber optic illuminators Staring arrays Quantum efficiency Sensors

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ANGULAR-MOMENTUM AND BALLISTIC tracking

ANGULAR-MOMENTUM AND BALLISTIC TRACKING

引用

4TH CONF ON THE SIGNAL AND DATA PROCESSING OF SMALL TARGETS 1992

作者： KOLBE, RL Naval Research Lab. (United States)

ISBN: (纸本)0819408638

The correlation and tracking problem for ballistic objects is a major concern for the Strategic Defense Initiative (SDI). In this presentation, the use of angular momentum for gating and assignment of reports and tracks of ballistic objects is proposed. The various errors and appropriate statistical tests that could be used on angular momentum to potentially improve the tracking and correlation, multi-track hypothesis and Kalman filters are studied. The investigation is performed in earth centered inertial Cartesian coordinates for position, velocity, and acceleration in tracking, gating, and assignment. A discussion is given of a brief investigation, the theory developed, the results of numerical test, and the conclusions.

关键词： Error analysis detection and tracking algorithms Filtering (signal processing) Data processing Signal processing Evolutionary algorithms Algorithm development Defense and security Ions Nonlinear filtering

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TRACK MONITORING WITH SINGLE AND MULTIPLE 2-D PASSIVE SENSORS

TRACK MONITORING WITH SINGLE AND MULTIPLE 2-D PASSIVE SENSOR...

引用

4TH CONF ON THE SIGNAL AND DATA PROCESSING OF SMALL TARGETS 1992

作者： ROECKER, JA IBM/Federal Sector Div. (United States)

ISBN: (纸本)0819408638

In a multiple target environment, hit-to-track data association is important for properly tracking targets in view. Track monitoring is a fast method of determining whether the proper data association has been made. This paper presents track monitoring algorithms for both single and multiple passive 2-D sensors along with analytical methods of evaluating their effectiveness. Single sensor track monitoring produces a dilemma: a poor track is a result of target maneuver or incorrect hit-to-track data association. The algorithm presented for multiple 2-D passive sensors solves the problem by adding inclination angle monitoring. The multiple sensor monitoring system can distinguish between target maneuver, incorrect hit-to-track data association, and the addition problem with multiple sensors of incorrect track-to-track association, or `ghost' tracks. These monitoring methods can be used to prune poor hypotheses in MHT filters or in single assignment tracking when processor power is limited.

关键词： Sensors Passive sensors Data processing Electronic filtering Environmental sensing Signal processing Digital filtering Filtering (signal processing) detection and tracking algorithms Testing and analysis

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INNOVATIVE TESTBED FOR DEVELOPING AND ASSESSING AIR-TO-AIR NONCOOPERATIVE TARGET IDENTIFICATION (NCTI) algorithms

INNOVATIVE TESTBED FOR DEVELOPING AND ASSESSING AIR-TO-AIR N...

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CONF ON SIGNAL PROCESSING, SENSOR FUSION, AND TARGET RECOGNITION

作者： KNOPOW, JP TAU Corp. (United States)

ISBN: (纸本)0819408646

The development and evaluation of multi-source, multi-spectral, all-aspect airborne target identification algorithms has been proven to be cumbersome as well as disjointed. The algorithm development capability under this testbed concept encompasses model-based reasoning, information fusion, airborne target identification, and target/sensor phenomenology analysis. The evaluation capability assembles multiple sensor and target types coupled with all aspect viewing in an operationally representative air-to-air environment. The importance of developing better techniques for establishing positive target identification for beyond visual ranges has increased in tactical importance, as a result of the Persian Gulf War. In addition to supporting the evaluation of algorithms and associated sensors, this testbed will support on- going R&D in the Air-To-Air Non-Cooperative Target Recognition (NCTR) arena.

关键词： Sensors Target recognition detection and tracking algorithms Algorithm development Electro optical modeling Environmental sensing Infrared signatures Data modeling Information fusion Visualization

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