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检索条件"任意字段=IET Conference on Data Fusion and Target Tracking 2014: Algorithms and Applications"

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iet conference on data fusion and target tracking 2014: algorithms and applications

IET Conference on Data Fusion and Target Tracking 2014: Algo...

引用

iet conference on data fusion and target tracking 2014: algorithms and applications

ISBN: (纸本)9781849198639

The proceedings contain 12 papers. The topics discussed include: Bayesian tracking and multi-core beamforming for estimation of correlated brain sources;particle filtering for network-based positioning terrestrial radio networks;tracking simulated UAV swarms using particle filters;rectangular extended object tracking with box particle filter using dynamic constraints;probabilistic step and turn detection in indoor localization;fusing kinect sensor and inertial sensors with multi-rate kalman filter;piecewise constant sequential importance sampling for fast particle filtering;hybrid gauss-hermite filter;regional variance in target number: analysis and application for multi-Bernoulli point processes;combined evidential data association;and PHD filtering in presence of highly structured sea clutter process and tracks with extent.

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Design and implementation of multi-feature fusion kernel correlation filtering algorithm based on HLS 5

Design and implementation of multi-feature fusion kernel cor...

引用

iet International Radar conference 2020, iet IRC 2020

作者： Cong, Peiyu Xie, Min Yang, Kaiming Zhang, Xiaofeng Su, Hongyan Fu, Xiongjun School of Information and Electronics Beijing Institute of Technology Beijing China Science and Technology on Millimeter-Wave Laboratory Beijing Institute of Remote-Sensing Equipment Beijing China

ISBN: (纸本)9781839535635

In order to balance the accuracy and real-time performance of the moving target tracking system, an optimized design and implementation method based on high-level synthesis (HLS) of multi-feature fusion with kernel correlation filtering algorithms on FPGA is designed. This design improves the KCF algorithm with LBP and HOG features, and proposes a new dimensionality reduction method for LBP, which enhances the real-time performance while maintaining effective extraction of target features. The algorithm is implemented with FPGA, and a well acceleration effect is obtained on the basis of high precision. In test, the frame rate reaches 35 frames per second. Finally, it is verified through simulation that this feature extraction method can be used to process various image data such as infrared detection and SAR radar imaging, and has a wide range of applications. © 2020 Institution of Engineering and Technology. All rights reserved.

关键词： Field programmable gate arrays (FPGA)

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Design and implementation of multi-feature fusion kernel correlation filtering algorithm based on HLS

Design and implementation of multi-feature fusion kernel cor...

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iet International Radar conference (iet IRC 2020)

作者： P. Cong M. Xie K. Yang X. Zhang H. Su X. Fu Beijing Institute of Technology Beijing China Beijing Institute of Remote-sensing Equipment Beijing China

关键词： target tracking filtering theory feature extraction image fusion synthetic aperture radar field programmable gate arrays object detection radar imaging

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Performance of target tracking in Radar Network System Under Deception Attack 10th

Performance of Target Tracking in Radar Network System Under...

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10th International conference on Wireless algorithms, Systems, and applications (WASA)

作者： Yang, Chaoqun Zhang, Heng Qu, Fengzhong Shi, Zhiguo Zhejiang Univ Hangzhou 310003 Zhejiang Peoples R China Huaihai Inst Technol Lianyungang Peoples R China

ISBN: (纸本)9783319218373;9783319218366

This paper studies security issue of target tracking in radar network system. We first derive the analytical result for the attack's effect on the performance of target tracking when one radar station is under deception attack. Based on this, by extending to radar network system, we find the relationship between the performance of target tracking and attack parameter. Simulation is presented to demonstrate the effectiveness of our results.

关键词： target tracking Deception attack Radar network system data fusion

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data fusion for a Vision-Radiological System: a Statistical Calibration Algorithm 4

Data Fusion for a Vision-Radiological System: a Statistical ...

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4th International conference on Advancements in Nuclear Instrumentation Measurement Methods and their applications (ANIMMA)

作者： Enqvist, Andreas Koppal, Sanjeev Riley, Phillip Univ Florida Gainesville FL 32611 USA

ISBN: (纸本)9781479999187

Presented here is a fusion system based on simple, low-cost computer vision and radiological sensors for tracking of multiple objects and identifying potential radiological materials being transported or shipped. The main focus of this work is the development of calibration algorithms for characterizing the fused sensor system as a single entity. There is an apparent need for correcting for a scene deviation from the basic inverse distance-squared law governing the detection rates even when evaluating system calibration algorithms. In particular, the computer vision system enables a map of distance-dependence of the sources being tracked, to which the time-dependent radiological data can be incorporated by means of data fusion of the two sensors' output data.

关键词： Computer vision

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9th iet data fusion and target tracking conference, DF and TT 2012: algorithms and applications

9th IET Data Fusion and Target Tracking Conference, DF and T...

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9th iet data fusion and target tracking conference: algorithms and applications, DF and TT 2012

ISBN: (纸本)9781849196246

The proceedings contain 16 papers. The topics discussed include: box-particle intensity filter;Gaussian mixture PHD filter for multi-target tracking using passive Doppler-only measurements;video analytics: past, present, and future;decentralised road-map assisted ground target tracking using a team of UAVs;a Bayesian look at the optimal track labelling problem;performance of bearing-only ESM-radar track association;Bayes optimal knowledge exploitation for target tracking with hard constraints;person tracking via audio and video fusion;optimized instrumental density for particle filter in track-before-detect;track degradation as a consequence of distributed sensor fusion;particle learning methods for state and parameter estimation;unsupervised learning of maritime traffic patterns for anomaly detection;and tracking and managing real world electric vehicle power usage and supply.

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Combined evidential data association

Combined evidential data association

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iet conference on data fusion and target tracking 2014: algorithms and applications

作者： Dallil, A. Ecole Militaire Polytechnique Algeria

ISBN: (纸本)9781849198639

In this paper, we present a new method for data association in multi-target tracking situation in the framework of evidence theory. The representation and the fusion of the information in our method are based on the use of belief function in the sense of Dempster-Shafer theory of evidence. The proposal generates two belief matrices using two different specialized basic belief mass assignments. While the decision making process is based on the extension of the frame of hypotheses. The method has been tested for a nearly constant velocity target in two ambiguous cases using Monte Carlo simulations.

关键词： target tracking

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tracking simulated UAV swarms using particle filters

Tracking simulated UAV swarms using particle filters

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iet conference on data fusion and target tracking 2014: algorithms and applications

作者： Easthope, P.F. L-3 Communications ASA Ltd Rusint House Fleet Hampshire GU51 2QS United Kingdom

ISBN: (纸本)9781849198639

This paper provides an initial examination of the use of particle filters in tracking swarms of small targets such as Unmanned Aerial Vehicles using a radar. From the standpoint of conventional tracking solutions, such swarms present a severe challenge - due not only to the quasi-erratic motion of the UAVs relative to the swarm trajectory as a whole, but also from the effects of the small target size upon radar resolution and detection probability. It is shown here that a particle filter is capable of providing a stable track on the swarm centroid, although not the individual constituent UAVs.

关键词： Unmanned aerial vehicles (UAV)

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Rectangular extended object tracking with box particle filter using dynamic constraints

Rectangular extended object tracking with box particle filte...

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iet conference on data fusion and target tracking 2014: algorithms and applications

作者： Petrov, Nikolay Mihaylova, Lyudmila Gning, Amadou Department of Automatic Control and Systems Engineering University of Sheffield United Kingdom Department of Computer Science University College London United Kingdom

ISBN: (纸本)9781849198639

Extended objects generate multiple measurements and are characterised with their size or volume. They require methods able to deal with the data association problem and at the same time to estimate both their kinematic states and shape parameters. This paper presents a solution to the extended object tracking for rectangular extended objects, with the Box Particle filter (Box PF) approach. The Box PF is implemented based on dynamically calculated constraints. Promising results are demonstrated.

关键词： Bandpass filters

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tracking and data Segmentation Using a GGIW Filter with Mixture Clustering 17

Tracking and Data Segmentation Using a GGIW Filter with Mixt...

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17th International conference on Information fusion (fusion)

作者： Scheel, Alexander Granstrom, Karl Meissner, Daniel Reuter, Stephan Dietmayer, Klaus Univ Ulm Inst Measurement Control & Microtechnol D-89069 Ulm Germany Linkoping Univ Dept Elect Engn S-58183 Linkoping Sweden

ISBN: (纸本)9781479916344

Common data preprocessing routines often introduce considerable flaws in laser-based tracking of extended objects. As an alternative, extended target tracking methods, such as the Gamma-Gaussian-Inverse Wishart (GGIW) probability hypothesis density (PHD) filter, work directly on raw data. In this paper, the GGIW-PHD filter is applied to real world traffic scenarios. To cope with the large amount of data, a mixture clustering approach which reduces the combinatorial complexity and computation time is proposed. The effective segmentation of raw measurements with respect to spatial distribution and motion is demonstrated and evaluated on two different applications: pedestrian tracking from a vehicle and intersection surveillance.

关键词： Area measurement Complexity theory Kinematics Noise measurement target tracking Time measurement Volume measurement area measurement time measurement Volume measurement Noise measurement Complexity theory target tracking data partitioning kinematics tracking EXTENDED OBJECTS Filters

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