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检索条件"任意字段=14th Conference on Signal and Data Processing of Small Targets"

共 443 条记录，以下是171-180 订阅

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small target of sea surface detection algorithm research based on feature classification

Small target of sea surface detection algorithm research bas...

引用

International conference on signal processing Proceedings (ICSP)

作者： Lianqing Yu Yun Li Ning Wang Jin Jiang Nanjing Research Institute of Electronics Technology Nanjing 210039 China

ISBN: (纸本)9781479921898

this paper focuses on small target of sea surface detection in sea clutter. Firstly, it analyses the statistic of sea clutter. Secondly, three feature vectors (namely, RAA, RPH and RVE) are extracted, which is utilized to discriminate the sea clutter and targets, and then the time-Doppler curve is used to distinguish the multi-targets in order to finish the small target of sea surface detection. Finally, it analyses the trial data of some radar and shows that this algorithm can effectively distinguish the sea clutter and small target of sea surface. this paper provides a new approach for the ship-borne surveillance radar or marine radar to detect the small target of sea surface and antisubmarine warfare patrol.

关键词： Abstracts Doppler effect Logic gates

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Dual-Channel SAR Ground Moving Target Detection and Parameters Estimation

Dual-Channel SAR Ground Moving Target Detection and Paramete...

引用

International conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology

作者： H. Shabana Liu Fang Shuyu Xiang National Key Laboratory image perception and recognition Xidian University National Key Laboratory of Radar Signal Processing Xidian University

ISBN: (纸本)9781479929948

this paper proposes a new algorithm for imaging moving targets via estimating their motion parameters with dual channel synthetic aperture radar. Displaced phase center array (DPCA) antennas are used for clutter cancelation through which moving targets are detected. the range motion of a moving target induces a Doppler centroid shift and additional range walk, while the along-track motion changes the Doppler modulation rate. the Doppler centroid shift dislocates the moving target from its actual azimuth position, and the additional range walk deteriorates the imaging resolution. the slope angle of the range walk trajectory is estimated via Hough transform, then the range velocity can be obtained. Doppler parameters of the moving targets are estimated with the fractional Fourier transform (FrFT). In this way, both target range and azimuth velocities are acquired. Next, the moving targets are focused with one uniform imaging algorithm. Simulated data processing results are provided to demonstrate the effectiveness of the proposed algorithm.

关键词： Synthetic Aperture Radar (SAR) Ground moving target identification (GMTI) Hough transform Motion parameter estimation Displaced phase center antenna (DPCA) Fractional Fourier transform (FrFT)

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Design of Millimeter Wave Hybrid Beamforming Systems

Design of Millimeter Wave Hybrid Beamforming Systems

引用

IEEE Vehicular Technology conference

作者： Girim Kwon Yeonggyu Shim Hyuncheol Park Hyuck M. Kwon Department of Electrical Engineering Korea Advanced Institute of Science and Technology Department of Electrical Engineering and Computer Science Wichita State University

ISBN: (纸本)9781479944484

Millimeter wave (mmWave) signals experience a significant path-loss in free space. To overcome this weakness, a large number of antennas are needed to obtain a high beamforming gain. Although a large number of antennas can be implemented in small area due to the short wavelength, the digital beamforming techniques cannot be implemented easily due to the high complexity of hardwares. To solve this problem, the hybrid beamforming systems which have smaller number of radio frequency (RF) chains are proposed in the literature. Although the hybrid beamforming systems may achieve the spectral efficiencies of the digital beamforming systems closely, the spectral efficiency cannot be monotonically increase along with the number of data streams due to the limited scattering in mmWave channel. In this paper, we provide a guide for the design of mmWave hybrid beamforming systems. We find the optimal number of streams, and present the spectral efficiency achievable region in which the system guarantees the reliable communications with the lowest cost.

关键词： Radio frequency Array signal processing Receivers Transmitters Scattering MIMO Antennas

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small object detection via fast discrete Curvelet transform

Small object detection via fast discrete Curvelet transform

引用

25th SPIE conference on signal and data processing of small targets

作者： Valdez, Hector A. Lu, thomas T. Chao, Tien-Hsin Calif State Univ Long Beach Long Beach CA 90840 USA CALTECH Jet Prop Lab 4800 Oak Grove Dr Pasadena CA 91125 USA

ISBN: (纸本)9780819497079

this paper describes the Fast Discrete Curvelet Transform (FDCT) which is integrated into an automated object detection framework capable of fast image processing for the purpose of tracking multiple objects of interest. the distinguishing difference between FDCT and other transforms is that the Curvelet coefficients have three beneficial parameters, which define scale, orientation, and spatial locations. We utilize these parameters to efficiently detect relatively small objects in a variety of image and video data sets. We have implemented the FDCT in a multi-stage automatic target recognition (ATR) architecture. the results of the current algorithm yield a highly sensitive detection of small targets in noisy backgrounds.

关键词： ATR Curvelet object detection ROI sparse representation targeting

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An Examination of the Application of Space Time Adaptive processing for the Detection of Maritime Surface targets from High Altitude Airborne Platforms

An Examination of the Application of Space Time Adaptive Pro...

引用

25th SPIE conference on signal and data processing of small targets

作者： McDonald, Michael Cerutti-Maori, Delphine Def R&D Canada 3701 Carling Ave Ottawa ON Canada Fraunhofer FHR D-53343 Wachtberg Germany

ISBN: (纸本)9780819497079

An examination of the application of Space Time Adaptive processing (STAP) techniques to real, multi-channel, medium grazing angle, radar sea clutter data is undertaken and the detection performance is quantified against simulated moving maritime surface targets. the application of sub-optimal STAP approaches to the maritime radar detection problem is shown to be complicated by non-stationarity of sea clutter and rapid variations of the sea clutter spectrum due to transient wave activity. Observed performance gains from maritime STAP are much more limited than those observed for Ground Moving Target Indication (GMTI) due to the inherent spectral width of sea clutter and the slow Doppler velocities of maritime targets. three sub-optimal STAP processing architectures are examined and PRI-Staggered Post-Doppler is shown to provide consistently superior detection performance for the data set in question.

关键词： Maritime surveillance STAP Radar GMTI

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Identification of Human Motion Signature using Airborne Radar data

Identification of Human Motion Signature using Airborne Rada...

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25th SPIE conference on signal and data processing of small targets

作者： McDonald, Michael Damini, Anthony Def R&D Canada Ottawa ON Canada

ISBN: (纸本)9780819497079

data containing the radar signature of amoving person on the ground were collected at ranges of up to 30 km from a moving airborne platform using the DRDC Ottawa X-band Wideband Experimental Airborne Radar (XWEAR). the human target radar echo returns were found to possess a characteristic amplitude modulated (AM) and frequency modulated (FM) signature which could be usefully characterized in terms of conventional AM and FM modulation parameters. Human detection performance after space time adaptive processing is frequently limited by false alarms arising from incomplete cancellation of large radar cross-section discretes during the whitening step. However, the clutter discretes possess different modulation characteristics from the human targets discussed above. the ability of pattern classification techniques to use this parameter measurement space to distinguish between human targets and clutter discretes is explored and preliminary results presented.

关键词： STAP Radar GMTI

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Detection of unusual trajectories using multi-objective evolutionary algorithms and rough sets

Detection of unusual trajectories using multi-objective evol...

引用

25th SPIE conference on signal and data processing of small targets

作者： Smolinski, Tomasz G. Newell, Trevor McDaniel, Samantha Pokrajac, David Delaware State Univ Dept Comp & Informat Sci Dover DE 19901 USA

ISBN: (纸本)9780819497079

Detection of unusual trajectories of moving objects (e.g., people, automobiles, etc.) is an important problem in many civilian and military surveillance applications. In this work, we propose a multi-objective evolutionary algorithms and rough sets-based approach that breaks down 2-dimensional trajectories into a set of additive components, which then can be used to build a classifier capable of recognizing typical, but yet unseen trajectories, and identifying those that seem suspicious.

关键词： Detection of Unusual Trajectories data Mining Evolutionary Algorithms Rough Sets

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Particle Filter Tracking for the Banana Problem

Particle Filter Tracking for the Banana Problem

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25th SPIE conference on signal and data processing of small targets

作者： Romeo, Kevin Willett, Peter Bar-Shalom, Yaakov Univ Connecticut Dept Elect & Comp Engn Storrs CT 06269 USA

ISBN: (纸本)9780819497079

In this paper we present an approach for tracking with a high-bandwidth active sensor in very long range scenarios. We show that in these scenarios the extended Kalman filter is not desirable as it suffers from major consistency problems;and most flavors of particle filter suffer from a loss of diversity among particles after resampling. this leads to sample impoverishment and the divergence of the filter. In the scenarios studied, this loss of diversity can be attributed to the very low process noise. However, a regularized particle filter is shown to avoid this diversity problem while producing consistent results. the regularization is accomplished using a modified version of the Epanechnikov kernel.

关键词： Particles Particle filters Detection and tracking algorithms Filtering (signal processing) Gaussian filters Digital filtering Error analysis Sensors Active sensors Statistical analysis

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On Covariance Structure in Noisy, Big data

On Covariance Structure in Noisy, Big Data

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25th SPIE conference on signal and data processing of small targets

作者： Paffenroth, Randy C. Nong, Ryan Du Toit, Philip C. Numerica Corp Loveland CO 80538 USA

ISBN: (纸本)9780819497079

Herein we describe theory and algorithms for detecting covariance structures in large, noisy data sets. Our work uses ideas from matrix completion and robust principal component analysis to detect the presence of low-rank covariance matrices, even when the data is noisy, distorted by large corruptions, and only partially observed. In fact, the ability to handle partial observations combined with ideas from randomized algorithms for matrix decomposition enables us to produce asymptotically fast algorithms. Herein we will provide numerical demonstrations of the methods and their convergence properties. While such methods have applicability to many problems, including mathematical finance, crime analysis, and other large- scale sensor fusion problems, our inspiration arises from applying these methods in the context of cyber network intrusion detection.

关键词： Sensors Matrices Computer networks Algorithms Computer intrusion detection Optimization (mathematics) Principal component analysis Sensor fusion data fusion Veins

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A Minimalist Approach to Bias Estimation for Passive Sensor Measurements with targets of Opportunity

A Minimalist Approach to Bias Estimation for Passive Sensor ...

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25th SPIE conference on signal and data processing of small targets

作者： Belfadel, Djedjiga Osborne, Richard W., III Bar-Shalom, Yaakov Univ Connecticut Dept Elect & Comp Engn Storrs CT 06269 USA

ISBN: (纸本)9780819497079

In order to carry out data fusion, registration error correction is crucial in multisensor systems. this requires estimation of the sensor measurement biases. It is important to correct for these bias errors so that the multiple sensor measurements and/or tracks can be referenced as accurately as possible to a common tracking coordinate system. this paper provides a solution for bias estimation for the minimum number of passive sensors (two), when only targets of opportunity are available. the sensor measurements are assumed time-coincident (synchronous) and perfectly associated. Since these sensors provide only line of sight (LOS) measurements, the formation of a single composite Cartesian measurement obtained from fusing the LOS measurements from different sensors is needed to avoid the need for nonlinear filtering. We evaluate the Cramer-Rao Lower Bound (CRLB) on the covariance of the bias estimate, i.e., the quantification of the available information about the biases. Statistical tests on the results of simulations show that this method is statistically efficient, even for small sample sizes (as few as two sensors and six points on the trajectory of a single target of opportunity). We also show that the RMS position error is significantly improved with bias estimation compared with the target position estimation using the original biased measurements.

关键词： Bias estimation bias observability statistical efficiency CRLB composite measurements maximum likelihood

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