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

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Track-to-track fusion in a multisensory environment

Track-to-track fusion in a multisensory environment

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Conference on Signal Processing, Sensor Fusion, and Target Recognition X

作者： Gendron, D Farooq, M Benameur, K Royal Mil Coll Canada Dept Elect & Comp Engn Kingston ON K7K 7B4 Canada

ISBN: (纸本)0819440752

Multiple-sensor data fusion is becoming increasingly important among the defence community as technology evolves. The use of multiple-sensor information reduces the ambiguity and presents the operator with an enhanced tactical picture of the surveillance volume. The crucial step in the fusion process is the data association of the information received from the sensors. If the associations are made incorrectly then the fused data could potentially give rise to estimates that might be worse than those of a single sensor. In this paper, we explore the problem of associating Electronic Support Measure (ESM) tracks with one or more possible radar tracks. We examine the performance of different track-to-track data association algorithms through simulations, which is based on the Probability of False Association (P-fa) and Probability of Correct (P-c) association.

关键词： Radar Electronic support measures Sensors Filtering (signal processing) detection and tracking algorithms Error analysis Data fusion Monte Carlo methods Data processing Surveillance

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Object identification and orientation estimation from contours based on an affine invariant curvature

Object identification and orientation estimation from contou...

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Intelligent Robots and Computer Vision VI 1987

作者： Cyganski, David Orr, John A. Cott, T. Andrew Dodson, Reynold J. Electrical Engineering Department Worcester Polytechnic Institute WorcesterMA01609 United States

New methods of image matching and of calculation of the affine transformation relating two images of an object in different orientations are developed. These methods are applicable to contours extracted from images of planar-patch objects. The approach is based on a new definition of a curvature function (previously developed by the authors) which is invariant to all image distortions representable by affine transformations. The algorithm is implemented and tested using camera-acquired images of actual objects, and is seen to exhibit considerable robustness to real-world distortions in the imaging process, as well as to deviations from planarity of the objects. © 1988 SPIE. All rights reserved.

关键词： Cameras Robot vision Algorithm development Image processing Computer vision technology Machine vision detection and tracking algorithms Feature extraction Quantization Correlation function

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An accelerated exploitation differential evolution algorithm for parameter estimation of photovoltaic models 6

An accelerated exploitation differential evolution algorithm...

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6th International Conference on Wireless Communications and Smart Grid, ICWCSG 2024

作者： Xu, Kezheng Yang, Qiangda Yuan, Shufu Ji, Yuzhang Chen, Yongxu School of Metallurgy Northeastern University Shenyang110819 China

ISBN: (纸本)9781510682962

The accurate recognition of parameters in the photovoltaic (PV) model is crucial for the assessment, adjustment, and tracking of the maximum power point in the PV system, which has significant theoretical and practical value. This paper proposes an adaptive differential evolution with an accelerated exploitation mechanism (AESHADE) for estimating parameter in PV models. In AESHADE, the algorithm's parameters fully utilize the historical evolutionary information of successful individuals and make adaptive adjustments. During the exploitation phase, when the algorithm stagnates, parameters are adjusted to accelerate convergence. To validate the efficacy of AESHADE, it is applied to the single diode model (SDM), double diode model (DDM), triple diode model (TDM), and Photowatt-PWP201 module model (PhotowattPWP201 MM). The experimental results demonstrate that, compared to seven others optimization algorithms, the AESHADE algorithm exhibits superior problem-solving precision on PV models. © 2024 SPIE.

关键词： Photovoltaics Diodes Solar cells Data modeling Control systems detection and tracking algorithms Mathematical optimization

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GSTAMIDS ground-penetrating radar: Data processing algorithms

GSTAMIDS ground-penetrating radar: Data processing algorithm...

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Conference on detection and Remediation Technologies for Mines and Minelike Targets VI

作者： Sower, GD Kilgore, R Roman, JR EG&G Tech Serv Albuquerque NM 87106 USA

ISBN: (纸本)0819440892

The Ground StandoffMine detection System (GSTAMIDS) is now in the Engineering, Manufacturing and Development (EMD) Block 0 phase for USA CECOM1. This paper describes the data processing algorithms for the GPR that are used to extract the features used for anti-tank (AT) mine detection;those used for pre-processing the data are included herein to show the enhancement of the mine signals. A key feature of the processing is the acquisition of a clean radar return signal from undisturbed soil, which is then deconvolved from each data frame waveform. This soil signal is an estimate of the system impulse response function, save for the magnitude of the reflection coefficient of the soil, which is a scalar to first order. Deconvolution thus gives the impulse response function of the buried mines, a strong enhancement over their raw measured signals. A matched filter test statistic is generated to discriminate between mines and background. Discrimination algorithms using hidden Markov model processing are described in a paper by P. D. Gader et al(3). These processes were developed in MATLAB(R) using data files acquired and stored from prototype GPR systems and then refined with data from production units. The MATLAB code is then converted into C code for use on the real-time processor on GSTAMIDS. The C code modules are run as dynamic library links (DLLs) in MATLAB for verification. The GPR sensor suite hardware and its physical incorporation into the GSTAMIDS sensor modules are described fully in a companion paper(2)..

关键词： Mining General packet radio service Sensors Land mines Deconvolution Data acquisition Data processing detection and tracking algorithms Reflection Signal processing

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Mask Manufacturing Rule Check:: How to save money in your mask shop

Mask Manufacturing Rule Check:: How to save money in your ma...

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20th Annual BACUS Symposium on Photomask Technology

作者： Keck, M Ziegler, W Liebe, R Franke, T Ballhorn, G Köfferlein, M Thiele, J Infineon Technol AG D-81617 Munich Germany

ISBN: (纸本)0819438499

By approaching the physical resolution limits of optical lithography for a given wavelength, data complexity on certain layers of chip layouts increases, while feature sizes decrease. This becomes even more apparent when introducing optical enhancement techniques. At the same time, more and more complex procedures to fracture mask data out of a DRC clean chip-GDS2 require checks on mask data regarding integrity, as well as mask manufacturability and inspectability. To avoid expensive redesigns and large mask house cycle times it is important to find shortcomings before the data are submitted to the mask house. As an approach to the situation depicted, a (Mask) Manufacturing Rule Check (MRC) can be introduced. Aggressive Optical Proximity Correction (OPC) is a special challenge for mask making. Recently, special algorithms for mask inspection of OPC assist features have been implemented by equipment vendors. Structures smaller than two inspection pixels, like assist structures, can be successfully inspected with certain algorithms. The impact of those algorithms on mask pattern requirements and suitable MRC adoptions will be discussed in the present paper.

关键词： Inspection Photomasks Manufacturing Optical proximity correction Bridges Computed tomography detection and tracking algorithms Inspection equipment Silver Tungsten

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On-line fringe tracking and prediction at IOTA

On-line fringe tracking and prediction at IOTA

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18th Congress of the International Commission for Optics - Optics for the Next Millennium

作者： Wilson, E Mah, R NASA Ames Res Ctr Smart Syst Lab Informat Sci Div Moffett Field CA 94035 USA

ISBN: (纸本)0819432342

The Infrared/Optical Telescope Array (IOTA) is a multi-aperture Michelson interferometer located on Mt. Hopkins near Tucson, Arizona. To enable viewing of fainter targets, an on-line fringe tracking system is presently under development at NASA Ames Research Center. The system has been developed off-line using actual data from IOTA, and is presently undergoing on-line implementation at IOTA. The system has two parts: (1) a fringe tracking system that identifies the center of a fringe packet by fitting a parametric model to the data;and (2) a fringe packet motion prediction system that uses characteristics of past fringe packets to predict fringe packet motion. Combined, this information will be used to optimize online the scanning trajectory, resulting in improved visibility of faint targets. Fringe packet identification is highly accurate and robust (99% of the 4000 fringe packets were identified correctly, the remaining 1% were either out of the scan range or too noisy to be seen) and is performed in 30-90 milliseconds (depending on desired accuracy) on a Pentium II-based computer. Fringe packet prediction, currently performed using an adaptive linear predictor, delivers a 10% improvement over the baseline of predicting no motion.

关键词： Data centers Data modeling Motion models detection and tracking algorithms Infrared telescopes Phase shifts Infrared radiation System identification Telescopes Visibility

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Utilizing high spatiotemporal resolution lightning observation data for thunderstorm identification 9

Utilizing high spatiotemporal resolution lightning observati...

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9th International Symposium on Advances in Electrical, Electronics, and Computer Engineering, ISAEECE 2024

作者： Zhang, Xi Luo, Fei Luo, Qian Zhi, Yaoling Wu, Huali Lu, Bingfu College of Software Engineering Chengdu University of Information Technology Sichuan Chengdu China Guangxi Lightning Protection Center Guangxi China

ISBN: (纸本)9781510683303

Thunderstorm weather has a significant impact on human society, and the precise identification of thunderstorm processes is crucial for thunderstorm weather prediction and the reduction of thunderstorm-related disasters. Existing research on thunderstorm identification methods is mainly divided into two categories: those based on radar detection data and those based on lightning location data. However, current studies suffer from large identification errors and an inability to effectively reflect the shape and boundaries of thunderstorms. To address these issues, this paper proposes a high spatiotemporal resolution thunderstorm identification method based on lightning location data. The method utilizes DBSCAN for identifying thunderstorm clusters and subsequently employs Alpha Shapes to extract boundaries. The proposed method is evaluated through optimal parameter selection and comparative experiments using a lightning location dataset from the Guangxi region. The results indicate that the performance of the new method in thunderstorm identification far surpasses that of existing methods. © 2024 SPIE.

关键词： Lightning detection and tracking algorithms Picosecond phenomena Reflectivity Radar sensor technology Radar Spatial resolution Absorbance Reflection Seaborgium

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Boundaries as unpredictable discontinuities

Boundaries as unpredictable discontinuities

引用

Image Understanding and the Man-Machine Interface II 1989

作者： Gleeson, Richard J. Skrzypek, Josef Machine Perception Laboratory Computer Science Department University of California Los AngelesCA90024 United States 3532D Boelter Hall UCLA Los AngelesCA90024 United States

A large part of the information content of an image is conveyed by the location of pixels that determine the boundaries between different segments. In absence of prior knowledge about objects in the scene, it is impossible to predict where the edges will occur. The gray levels at locations away from boundaries are often highly correlated. They can be estimated from the values of nearby locations using assumptions based on our knowledge of the physical laws governing reflections from surfaces. Boundaries occur at points of essentially infinite variation. At these points corresponding gray levels result from summing energy reflected by two different regions and cannot be easily estimated from the values at nearby pixels. In this sense gray level values at discontinuities are less predictable.

关键词： Edge detection Error analysis Image understanding detection and tracking algorithms Interfaces Image processing Image segmentation Reflection Sensors Signal to noise ratio

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DNN performance optimization based on Gemmini neural network hardware accelerator 4

DNN performance optimization based on Gemmini neural network...

引用

4th International Conference on Advanced algorithms and Neural Networks, AANN 2024

作者： Zhao, Denghui He, Jianrui Jing, Xuyu Hou, Xibiao AVIC Xi’an Flight Automatic Control Research Institute Aviation Key Laboratory of Science and Technology on Aircraft Control Xi’an710065 China

ISBN: (纸本)9781510686106

Gemmini is an open-source, full-stack DNN accelerator generator. For an DNN algorithm running on Gemmini, traditional optimizations focus on changing Gemmini's hardware configuration (e.g., changing the size of internal storage and the size of the systolic array). This work proposes an an optimization-test iteration route combining Spike simulation and FPGA simulation under the constraints of unacceptable running speed of verilator simulator and limited FPGA resources. According to this route, this work starts from two aspects of hardware optimization and algorithm optimization. The internal storage size and calculation scale of Gemmini are changed in hardware, and the convolutional layer of Resnet50 neural network algorithm is optimized in algorithm. The experimental results show that for Resnet50 DNN algorithm, Gemmini with basic configuration provides 2000x speedup compared with running on CPU. On the platform of Gemmini accelerator, the optimization of hardware configuration provides 1.59x speedup for Resnet50. On the basis of the hardware optimization, the algorithm optimization provides 1.012x speedup. © 2024 SPIE.

关键词： Mathematical optimization Neural networks Field programmable gate arrays Data storage Evolutionary algorithms Convolution detection and tracking algorithms Performance modeling Matrices

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Modulation Recognition Method of Wireless Communication Digital Signal Considering Multi-dimensional Characteristics

Modulation Recognition Method of Wireless Communication Digi...

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2021 International Conference on Network Communication and Information Security, ICNCIS 2021

作者： Yu, Qianfan Guo, Yanyun School of Applied Science and Technology Hainan University Hainan Danzhou571700 China Beijing Railway Electrification College Beijing102202 China

ISBN: (数字)9781510653283

ISBN: (纸本)9781510653276

Modulation recognition is a key technology in the field of communication, especially in the field of non cooperative communication. It can realize the automatic recognition and classification of unknown signal modulation without prior knowledge. With the rapid development of modern communication technology, modulation methods become complex and diverse, and modulation recognition technology is also facing more challenges. Although there are relevant studies, there are still many problems and research work to be solved and improved. Based on this, a modulation recognition method of wireless communication digital signal considering multi-dimensional characteristics is proposed. By extracting multidimensional characteristic parameters, constructing multi-dimensional characteristic signal modulation decision tree model and wireless communication digital signal modulation recognition algorithm based on multi-dimensional characteristic model, the modulation mode recognition of digital signal is realized. The experiment shows that compared with the traditional methods, this recognition method has more advantages in the overall modulation recognition accuracy when the signal-to-noise ratio is rising. © 2022 SPIE

关键词： Modulation Multidimensional signal processing Data communications Wireless communications detection and tracking algorithms Signal to noise ratio Phase shift keying Data modeling Digital modulation Frequency shift keying

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