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检索条件"任意字段=13th Conference on Signal and Data Processing of Small Targets"

共 447 条记录，以下是61-70 订阅

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Fast mutual exclusion

Fast mutual exclusion

引用

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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Mobility and Traffic Prediction-Based Resource Allocation with Edge Intelligence in Wireless Network 13

Mobility and Traffic Prediction-Based Resource Allocation wi...

引用

13th International conference on Wireless Communications and signal processing, WCSP 2021

作者： Sun, Yukun Zhang, Xing Zhu, Yongdong Beijing University of Posts and Telecommunications Wireless Signal Processing and Network Laboratory Beijing100876 China Zhejiang Lab Zhejiang Province China

ISBN: (纸本)9781665407854

Radio resources are increasingly scarce with the explosive growth of smart end devices while these resources are under-utilized in existing wireless networks. Deep learning can make full use of wireless big data to predict information from both the user and network side. thus, predictive resource allocation applying intelligence learning at network edge is a promising approach to improve the system performance. In this paper, we formulate a prediction-based resource allocation policy (PBRA) with edge intelligence in a large time scale aiming to improve system throughput. A proportion factor is proposed to adapt to channel gains, user mobility and quality-of-service (QoS) with predictive information, which can be predicted by edge intelligence server deployed at network edge. then, we propose the PBRA algorithm in a small time scale with solved optimal policy in the large time scale. Simulation results show that the proposed PBRA policy achieves higher throughput and improves QoS even compared with fair proportion scheduling policy with error-free predictive information. © 2021 IEEE.

关键词： Forecasting

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Block-Division Based Ultra-wideband Fusion of Multiple Radar Bands for Resolution Enhanced Imagery 12

Block-Division Based Ultra-wideband Fusion of Multiple Radar...

引用

12th International conference on signal processing and Communication Systems (ICSPCS)

作者： Yuan, Saisai Chen, Chengzeng Xu, Xiaojian Beihang Univ Sch Elect & Informat Engn Beijing Peoples R China Beijing Inst Radio Measurement Beijing Peoples R China

ISBN: (纸本)9781538656020

Parametric model based ultra-wideband fusion of multiple radar band data is usually not directly applicable to radar image processing for large sized complex targets, due to the fact that the required model orders are extremely high. In this paper, a block-division based data fusion technique is proposed, which can be used for multiple radar band fusion over ultra-wide bandwidth and image resolution enhancement for complex targets. In image domain, a large sized complex target is first divided into small blocks for each radar band. Each block is then equivalent to a small sized simple target whose missing phase history data between two different radar bands can be interpolated based on parametric models derived from the measurement data of the corresponding bands. Resolution enhanced image can then be reconstructed by integrating all the image blocks generated from the multi-band fused data. Numerical examples are presented to demonstrate the usefulness of the proposed technique.

关键词： radar imaging ultra-wideband data fusion complex target block-division

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Simulation of signal and data processing for a pair of GEO IR sensors

Simulation of signal and data processing for a pair of GEO I...

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19th conference on signal and data processing of small targets

作者： Keil, Karl-Heinz Hupfer, Werner EADS Astrium GmbH Bremen Germany

ISBN: (纸本)9780819468475

this paper describes experiences and results from developing a basic signal and data processing simulation for a pair of GEO IR sensors observing the boost phase of theater Ballistic Missiles (TBM). the goal of such a system is the detection of launched TBM, also against a cloud background, and the tracking from cloud break ideally up to boost-end. Two GEO satellites are used for stereo view of one and the same non-global limited Field-of-Regard (FOR). they are positioned in such a way that both cover the FOR and provide a sufficient triangulation baseline. signal processing is applied for each of both passive IR sensors in order to detect and track the TBM on the focal plane. the applied approach can be summarized under the term 'velocity filtering'. data processing operates on the 2-D signal processing input from both IR sensors, i.e. azimuth and elevation line-of-sight (LOS) angles as well as their rates. the goal is to provide 3-D tracks of the targets, which can be used to cue early warning or fire control radars. the underlying simulation model constitutes a prototype and vehicle for further research. Nevertheless, even in its current stage it provides a first tool for the analysis and evaluation of corresponding sensor design concepts.

关键词： signal processing data processing Satellites Filtering (signal processing) Digital filtering Sensors Clouds Infrared sensors Target detection Optical filters

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Mobility-Aware Pre-caching Based on Unsupervised Deep Generative Model for small Cell Networks 13

Mobility-Aware Pre-caching Based on Unsupervised Deep Genera...

引用

13th IEEE International conference on signal processing and Communication Systems (ICSPCS)

作者： Yao, Zhen Chen, Shuangwu Yang, Jian Liu, Yifeng Xie, Haiyong Univ Sci & Technol China Hefei Peoples R China China Acad Elect & Informat Technol Beijing Peoples R China

ISBN: (纸本)9781728121949

Due to the short coverage of small-cell base stations (SBS), mobile device is more likely to move away from its covered area, and thus has to continually switch between SBSs and reestablish the connections with the remote servers. Aiming for improving the delivery efficiency of ever-growing mobile data traffic, we conceive proactive caching over dense small-cell network (DSCN). Without any prior knowledge, it is challenging to figure out users movements and determine content placement in SBSs. Motivated by the recent advances in deep learning, we first propose a model-free mobility prediction approach based on the conditional variational autoencoder (CVAE) in this paper. Our approach is able to infer the latent information about users habits, which are considered to be closely related to their movements, from historical trajectory. By testing on real-world GPS trajectories, our approach achieves a prediction accuracy of about 80%. then based on the movement prediction, we formulate an optimization problem to maximize the local cache utility for DSCN. the experimental results show that our mobility-aware pre-caching strategy can support a seamless mobility handover with a lower delay and a higher data rate.

关键词： Deep learning

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Exact methodology for testing linear system software using idempotent matrices and other closed-form analytic results

Exact methodology for testing linear system software using i...

引用

13th conference on signal and data processing of small targets

作者： Kerr, th TeK Associates Lexington MA USA

ISBN: (纸本)0819441872

We alert the reader here to a variety of structural properties associated with idempotent matrices that make them extremely useful in the verification/validation testing of general purpose control and estimation related software. A rigorous general methodology is provided here along with its rationale to justify use of idempotent matrices in conjunction with other tests (for expedient full functional coverage) as the basis of a coherent general strategy of software validation for these particular types of applications. the techniques espoused here are universal and independent of the constructs of particular computer languages and were honed from years of experience in crosschecking Kalman filter implementations in several diverse commercial and military applications. While standard Kalman filter implementation equations were originally derived by Rudolf E. Kalman in 1960 using the Projection theorem in a Hilbert Space context (with prescribed inner product related to expectations), there are now comparable Kalman filter results for systems described by partial differential equations (e.g., arising in some approaches to image restoration or with some distributed sensor situations for environmental toxic effluent monitoring) involving a type of Riccati-like PDE equation to be solved for the estimation error. the natural framework for such infinite dimensional PDE formulations is within a Banach Space (being norm-based) and there are generalizations of idempotent matrices similar to those offered herein for these spaces as well that allow closed-form test solutions for infinite dimensional linear systems to verify and confirm proper PDE implementations in S/W code. Other closed-form test case extensions discussed earlier by the author have been specifically tailored for S/W verification of multichannel maximum entropy power spectral estimation algorithms and of approximate nonlinear estimation implementations of Extended Kalman filtering and for Batch Least Squares (B

关键词： verification & validation of linear system software sub-modules using analytic closed-form results ODE's and PDE's trade-off's in batch filter use revised assessment of preferred squareroot filter implementations

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PHD filters of second order in target number

PHD filters of second order in target number

引用

18th conference on signal and data processing of small targets

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

ISBN: (纸本)0819462926

the multitarget recursive Bayes nonlinear filter is the theoretically optimal approach to multisensor-multitarget detection, tracking, and identification. For applications in which this filter is appropriate, it is likely to be tractable for only a small number of targets. In earlier papers we derived closed-form equations for an approximation of this filter based on propagation of a first-order multitarget moment called the probability hypothesis density (PHD). In a recent paper, Erdinc, Willett, and Bar-Shalom argued for the need for a PHD-type filter which remains first-order in the states of individual targets, but which is higher-order in target number. In an earlier paper at this conference we derived a closed-form cardinalized PHD (CPHD) filter, which propagates not only the PHD but also the entire probability distribution on target number. Since the CPHD filter has computational complexity O(m(3)) in the number m of measurements, additional approximation is desirable. In this paper we discuss a second-order approximation called the "binomial filter."

关键词： Digital filtering Nonlinear filtering Sensors Target detection Electroactive polymers Filtering (signal processing) Motion models Picosecond phenomena Electronic filtering Linear filtering

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Target classification with data from multiple sensors

Target classification with data from multiple sensors

引用

14th conference on signal and data processing of small targets

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

ISBN: (纸本)0819444782

the methods used in the classification of multiple small targets can be very different from the methods commonly used in traditional pattern recognition. First, there may be characteristics of the features for. each target class that can permit simpler computations than other features. In addition, in classifying targets, the target tracks are updated as new data becomes available and hence there can be a sequence of feature measurements that are available for the target classification process. In addition, with multiple targets, the a priori information may be in a form that make the classification processing for one target dependent on the classification processing of other targets. these aspects of target classification that make that processing different from traditional pattern recognition are the concern of this paper. To limit the length of the paper, the scope is restricted to classification tasks that allow the linear-Gaussian assumption to be used. Also, the data used in the classification process is restricted to features, i.e., no attributes, and the assumption is the tracker does not employ feature-aided tracking. While these assumptions simplify the discussion, the methods used could be modified to permit classification of a broad scope of classification tasks.

关键词： multiple target tracking features target typing detection classification recognition identification and discrimination automatic target recognition (ATR) multiple models Bayesian methods and Kalman filter

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data Acquisition System with Low-Accuracy Sensors 13

Data Acquisition System with Low-Accuracy Sensors

引用

13th International conference on Development and Application Systems (DAS)

作者： Jun, Su Roshchupkin, Oleksiy Kochan, Volodymyr Sachenko, Anatoliy Roshchupkina, Nataliia Hubei Univ Technol Sch Comp Sci Wuhan Peoples R China Czech Tech Univ Fac Elect Engn Prague Czech Republic Ternopil Natl Econ Univ Res Inst Intelligent Comp Syst Ternopol Ukraine Silesian Tech Univ Dept Comp Sci & Econometr Gliwice Poland Chernivtsi Natl Univ Comp Syst & Network Dept Chernovtsy Ukraine

ISBN: (纸本)9781509019939

the paper deals with improving the accuracy of the sensors under influence of non-informative factors. there are described the generalized block diagram of the data acquisition system and its measurement channels which provide the sensors signal processing. the generalized block diagram of the calculation process is proposed, and the structure of used neural networks is shown. Both scheme and algorithm of data processing are described. the measurement error of the proposed system was evaluated. It confirmed that proposed system adds the error of 0.32% which is very small in comparison with the etalon mean of 1%. the proposed system allows use of the sensors with a significant influence of non-informative factors.

关键词： Multisensor Sensor Neural Network Individual Transfer Function data Acquisition System Measuring Channels Algorithm

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An empirical large signal model for silicon carbide MESFETs

An empirical large signal model for silicon carbide MESFETs

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13th European Gallium Arsenide and Other Compound Semiconductors Application Symposium (GAAS 2005)

作者： Sayed, Ahmed Boeck, Georg Tech Univ Berlin Microwave Engn Grp D-10587 Berlin Germany

ISBN: (纸本)8890201207

In this paper, a large signal table-based model for SiC MESFET is presented. A packaged commercially available high power MESFET device (CREE CRF24010) is adopted for the model development. the extracted bias-dependent elements of the small signal model as well as the measured DC data are mathematically described by small modification of Angelov's formulation. Dispersion between DC and RF characteristics of the drain current is also,observed and interpreted. the new model is capable to predict small signal as well as large signal performance accurately. A single stage ultra broadband 5 W power amplifier has been developed to verify the derived model. A good agreement has been obtained between simulated and measured results.

关键词： MESFET devices

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