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检索条件"任意字段=Signal and Data Processing of Small Targets 1995 Conference"

共 783 条记录，以下是181-190 订阅

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Adaptive Kalman filter for tracking of fast accelerating targets

Adaptive Kalman filter for tracking of fast accelerating tar...

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European Radar conference (EURAD)

作者： Premysl Hudec Petr Panek Department of Electromagnetic Field Czech Technical University in Prague Prague 6 Czech Republic Academy of Sciences of the Czech Republic Institute of Photonics and Electronics Czech Republic

Active defense (AD) is a new method for protecting military vehicles. Instead of using thick and extremely heavy armors, the actively protected vehicles monitor approaching threatening missiles and de-active them by a suitable active counter-measures. The majority of AD systems is based on radar sensors capable of detecting the concerned missiles and measuring their parameters important for the protective functions. Often, these radar sensors are required to operate in a near-zone (from zero to tens of meters) and find and track relatively small and fast-flying targets. Beside that, it is necessary to take into account the fact that the velocity of the monitored targets can instantaneously vary. This problem especially refers to ignition of rocket engines which can abruptly introduce extremely high accelerations. If the concerned radar sensors employ signal-processing methods based on Kalman filtration, these high-order time-derivatives can cause substantial convergence problems. The main purpose of this article is to present the newly developed adaptable filtering which can reduce these effects. The designed procedures were verified using practically recorded data from flight of RPG-7 missiles.

关键词： Standards Estimation Radar Kalman filters Missiles Sensors Engines

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GMTI in circular SAR data using STAP 6

GMTI in circular SAR data using STAP

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conference on Sensor signal processing for Defence (SSPD)

作者： Casalini, Emiliano Henke, Daniel Meier, Erich Univ Zurich Remote Sensing Labs CH-8006 Zurich Switzerland

ISBN: (纸本)9781509003266

This paper presents method and results of a Ground Moving Target Indication (GMTI) experiment using multichannel Synthetic Aperture Radar (M-SAR) data collected by the four channel F-SAR system. The proposed approach is based on sub-aperture processing, Space-Time Adaptive processing (STAP), constant false alarm rate (CFAR) thresholding and geocoding. The results are validated and compared with results of the same data set from a previous approach based on a combination of single-channel (SC) and Along-Track Interferometry (ATI) detections. It is shown that the STAP-based technique guarantees better performances when detecting moving targets with a small Radar Cross Section (RCS).

关键词： Space time adaptive processing

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SISAR Imaging Method Based On GNSS signal:theory and experimental results

SISAR Imaging Method Based On GNSS Signal:theory and experim...

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CIE International conference on Radar (RADAR)

作者： Hu, Cheng Wang, Li Liu, Changjiang Beijing Inst Technol Sch Informat & Elect Beijing Key Lab Embedded Real Time Informat Proc Beijing Peoples R China

ISBN: (纸本)9781509048281

Shadow inverse synthetic aperture radar (SISAR) imaging technology is the basis for target recognition in forward scatter radar (FSR). The novel FSR system, which uses Global Navigation Satellite System (GNSS) satellites as transmitters and arranges receivers on the ground, has the ability to achieve target detection in a wide range. This paper proposes a novel SISAR imaging algorithm based on the GNSS signal and gives the relationship between the transform of GNSS-FSR echo signal and target's complex profile function (CPF) under small diffraction angles. The effectiveness of the proposed SISAR imaging algorithm is firstly verified by applying SISAR imaging processing to the experimental data which is obtained by using civil airliners as targets and BD satellite as the illuminator at the first time.

关键词： Forward scatter radar SISAR imaging GNSS passive radar

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Variable size small targets detection using density-based clustering combined with backtracking strategy 22

Variable size small targets detection using density-based cl...

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conference on Image and signal processing for Remote Sensing XXII

作者： Zhang, Haiying Lin, Yonggui Xiao, Fangxiong Xiamen Univ Software Sch Xiamen 361005 Peoples R China Guangxi Univ Finance & Econ Sch Informat & Stat Guangxi 530003 Peoples R China Jinling Inst Technol Sch Software Engn Nanjing 211169 Jiangsu Peoples R China

ISBN: (数字)9781510604131

ISBN: (纸本)9781510604124;9781510604131

The series problem of infrared small target detection in heavy clutter is a challenging work in active vision. During different imaging environments the size and gray intensity of target will keep changing which lead to unstable detection. Focus on mining more robust feature of small targets and following the sequential detection framework, we propose a novel research scheme based on density-based clustering and backtracking strategy in this paper. First, point of interest is extracted by the speeded up robust feature (SURF) detector for its better performance in digging features invariant to uniform scaling, orientation and illumination changes. Second, due to the local aggregation property of target trajectory in space, a new proposed density-based clustering method is introduced to segment the target trajectory, so that the target detection problem is transformed into the extract the target trajectory. Then, In order to keep the integral and independence of the trace as much as possible, two factors: percent and are exploited to help deciding the clustering granularity. Later, the backtracking strategy is adopted to search for the target trajectory with pruning function on the basis of the consistence and continuity of the short-time target trajectory in temporal-spatial. Extended experiments show the validity of our method. Compared with the data association methods executed on the huge candidate trajectory space, the time-consuming is reduced obviously. Additional, the feature detection is more stable for the use of SURF and the false alarm suppression rate is superior to most baseline and state-of-arts methods.

关键词： infrared small target SURF density-based clustering backtracking algorithm

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A high power EMI sensor for detecting and classifying small and deep targets 21

A high power EMI sensor for detecting and classifying small ...

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conference on Detection and Sensing of Mines, Explosive Objects, and Obscured targets XXI

作者： Shubitidze, F. Barrowes, B. E. Wang, Yinlin Shamatava, Irma Sigman, J. B. O'Neill, K. Steinhurst, Daniel A. Dartmouth Coll Thayer Sch Engn HB 8000 Hanover NH 03755 USA White River Technol Inc 3 Schoolhouse Ln Etna NH 03750 USA USA ERDC Cold Reg Res & Engn Lab Hanover NH 03755 USA Nova Res Inc Alexandria VA 22308 USA

ISBN: (纸本)9781510600645

Detecting and classifying small (i.e., with calibers ranging from 20 to 60 mm) and deep targets (burial depth more than 11 times targets diameter) is still a challenging problem using current advanced EMI sensors and signal processing approaches. In order to overcome this problem, the standard time-domain NRL TEMTADS 2x2 electromagnetic induction (EMI) instrument is updated. Namely, the NRL TEMTADS 2x2 system's transmitter electronics is modified to increase transmitter (Tx) currents from 6 Amperes to 14 Amperes. The instrument has a Tx array with four coplanar square coils, together with four tri-axial receivers (Rx) placed at the center of each Tx. Each Rx cube contains three orthogonal coils and thus registers all three vector components of the impinging signals. The Tx coils, with transmitter currents of similar to 14 A, illuminate a buried target, and the target responses are collected with a 500 kHz sample rate after turn off of the excitation pulse. The system operates in both static (cued) and dynamic modes. For cued mode, the raw decay measurements are grouped into 121 logarithmically-spaced " gates" whose center times range from 25 mu s to 24.35 ms with 5% widths. The sensor is placed on a cart which provides a sensor-to-ground offset of 20 cm or less. In this paper, studies for APG Calibration, Blind, and small Munitions Grids are presented and analyzed. The areas are arranged in grids of test cells and the cell center positions are known. Each target position is flagged with a non-metallic pin flag using cm-level GPS. The sensor is positioned over each target in turn. With the system positioned over the target, each Tx is activated sequentially and during off the Tx current, all four Rx record data. The capabilities of this sensor platform is rigorously investigated for UXO classification at APG blind and small munitions grids.

关键词： High Power detection classification UXO advanced models EMI Sensors ONVMS modeling APG test-site mini-Metal Mapper

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Underwater Threat Detection and Tracking using Multiple Sensors and Advanced processing 50

Underwater Threat Detection and Tracking using Multiple Sens...

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IEEE International Carnahan conference on Security Technology (ICCST)

作者： Meecham, Andy Acker, Tim Northern Def Ind Inc Alexandria VA 22314 USA BioSonics Inc Seattle WA USA

ISBN: (纸本)9781509010721

The vulnerability of military installations and critical infrastructure sites from underwater threats is now well accepted and, in order to combat these security weaknesses, there has been growing interest in - and adoption of - sonar technology. Greater availability of Autonomous/Unmanned Underwater Vehicles (A/UUVs) to both adversary nations and terrorists/saboteurs is also a cause of increasing concern. The small size and low acoustic target strength/signature of these vehicles presents significant challenges for sonar systems. The well-known challenges of the underwater environment, particularly in a harbor or port setting, can lead to a Nuisance Alarm Rate (NAR) that is higher than that of traditional security sensors (e.g. CCTV). This, in turn, can lead to a lack of confidence from end users and a possibility that real' alerts are incorrectly dismissed. In the past this has been addressed by increasing the capability of individual sensors, leading to ever-increasing sensor complexity, however, the relationship between sensor performance and complexity/cost is highly non-linear. Even with the most complex and capable sensors, the fundamental limit to performance is often limited by acoustics, not sensor capability. In this paper we describe an alternative approach to reducing NAR and improving detection of difficult targets (e.g. UUVs), through intelligent combination and fusion of outputs from multiple sensors and data/signal processing algorithms. We describe the statistical basis for this approach, as well as techniques, methodologies and architectures for implementation. We describe the approach taken in our prototype algorithms/system, as well as quantitative and qualitative results from testing in a real-world environment. These results show a significant reduction in NAR and increase in classification/alert range. Finally, we describe current focus areas for algorithmic and system development in both the short and medium term, as well as future extension

关键词： sonar maritime security UUV data fusion

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Assignment and EM Approaches for Passive Localization of Multiple Transient Emitters 25

Assignment and EM Approaches for Passive Localization of Mul...

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conference on signal processing, Sensor/Information Fusion, and Target Recognition XXV

作者： Doul, Wenbo George, Jemin Kaplan, Lance Osborne, Richard W., III Bar-Shalom, Yaakov Univ Connecticut Dept Elect & Comp Engn Storrs CT 06269 USA US Army Res Lab Adelphi MD USA

ISBN: (纸本)9781510600836

This paper investigates the problem of localizing an unknown number of transient emitters using a network of passive sensors measuring angles of arrival in the presence of missed detections and false alarms. It is assumed that measurements within a certain time window of interest have to be associated before they can be fused to estimate the emitter locations. Two measurement models either that any target can generate at most one measurement per sensor or that any target can generate several measurements per sensor are possible within this time window. These two measurement models lead to two different problem formulations: one is an S-D assignment problem and the other is a cardinality selection problem. The S-D assignment problem can be solved by the Lagrangian relaxation algorithm efficiently with a high degree of accuracy when a small number of sensors are used. The sequential m-best 2-D assignment algorithm, which is resistant to the ghosting problem due to the estimation of the emitter signal's emission time, is developed to solve the problem when the number of sensors becomes large. Simulation results show that the sequential m-best 2-D assignment algorithm is suitable for real time processing with reliable associations and estimates. The cardinality selection formulation models a list of measurements as a Poisson point process and is solved by applying the expectation-maximization (EM) algorithm and an information criterion. The convergence of the EM algorithm to the desired global maximum needs an initialization, which is close to the truth. Localization using passive sensors makes it difficult to obtain such an initial estimate. An assignment-based initialization approach is therefore presented. Simulation studies showed that the EM algorithm based on the assignment initialization is able to estimate the number of targets, target locations and directions with a high degree of accuracy.

关键词： Multiple target localization data association data fusion transient measurements passive sensors

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Improved adaptive co-pulse differential methods for nautical radar small target detection in sea clutter

Improved adaptive co-pulse differential methods for nautical...

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CIE International conference on Radar (RADAR)

作者： Bao, Zhonghua Xi, Zemin Lu, Jianbin Naval Univ Engn Elect Engn Coll Wuhan Peoples R China

ISBN: (纸本)9781509048281

Detection of small targets in sea clutter is an important issue for nautical radar signal processing. Firstly two improved adaptive co-pulse differential methods were presented in this paper, based on different modulation effects of radar antenna to small target and azimuth distributed sea clutter. Then the performance of the proposed methods was analyzed and the selection of optimum algorithm parameters was discussed. Considering that sea clutter's characteristic is random and time varying, the auto-relativity of sea clutter which was part of key algorithm parameters was estimated adaptively. Finally, field data acquired by a shore-based X-band non-coherent nautical radar was used to validate the proposed methods.

关键词： sea clutter small target detection co-pulse differential method adaptive processing

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DOMAIN ADAPTATION FOR SPEECH EMOTION RECOGNITION BY SHARING PRIORS BETWEEN RELATED SOURCE AND TARGET CLASSES

DOMAIN ADAPTATION FOR SPEECH EMOTION RECOGNITION BY SHARING ...

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IEEE International conference on Acoustics, Speech and signal processing

作者： Qirong Mao Wentao Xue Qiru Rao Feifei Zhang Yongzhao Zhan Department of Computer Science and Communication Engineering Jiangsu University China

ISBN: (纸本)9781479999897

In speech emotion recognition (SER), speech data is usually captured from different scenarios, which often leads to significant performance degradation due to the inherent mismatch between training and test set. To cope with this problem, we propose a domain adaptation method called Sharing Priors between Related Source and Target classes (SPRST) based on a two-layer neural network. The classifier parameters, namely the weights of the second layer, are imposed the common priors between the related classes, so that the classes with few labeled data in target domain can borrow knowledge from the related classes in source domain. The method is evaluated on the INTERSPEECH 2009 Emotion Challenge two-class task. Experimental results show that our approach significantly improves the performance when only a small number of target labeled instances are available.

关键词： Domain adaptation speech emotion recognition neural network priors Neural network emotion recognition Speech targets degradation of performance Classes Domain

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small and dim target detection by background modeling

Small and dim target detection by background modeling

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conference on signal and data processing of small targets

作者： Hu, Jing Yu, Yi Liu, Fan Huazhong Univ Sci & Technol Sch Automat Sci & Technol Multispectral Informat Proc Lab Wuhan 430074 Peoples R China

ISBN: (纸本)9781628417623

An effective method for small and dim moving target detection in complicated background is proposed. The proposed approach takes advantage of the Non-local means filter, and applies a novel weight calculation model based on circular mask to the original background estimation pattern. By associating similarity of grayscale distribution of the images with temporal information, the extended method realize the complicated background estimation and point target extraction successfully. To compare existing target detection methods and the proposed method, signal-to-clutter ratio gain (SCRG) and background suppression factor (BSF) are employed for spatial performance comparison and receiver operating characteristics (ROC) is used for detection-performance comparison of the target trajectory. Experimental results demonstrate good performance of the proposed method in complicated scenes and low signal to noise ratio images.

关键词： small and dim target detection complicated background background modeling Non-Local means

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