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检索条件"任意字段=Conference on Signal and Data Processing of Small Targets 2010"

共 976 条记录，以下是221-230 订阅

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The bottom reverberation suppression algorithm for Side Scan Sonar

The bottom reverberation suppression algorithm for Side Scan...

引用

Oceans conference

作者： Liu Jia Xu Feng Yang Juan An Xudong Chinese Acad Sci Inst Acoust Beijing Peoples R China

ISBN: (纸本)9781479949182

The sea bottom reverberation is one of the important problems, which restrict the bottom targets detection performance with the high frequency imaging sonar. In this paper, a bottom reverberation suppression algorithm is presented to improve the performance of the high frequency side scan sonar for small target detection. In the paper, the statistics characteristic of the target echo and the bottom reverberation is introduced, with the experiment data processing. The target echo and the bottom reverberation could be separated with the difference of the statistics characteristic. And the Blind Source Separated method was applied to implement the signal separation. At last, the effective of this method was proved by the process of the experiment data.

关键词： Side scan sonar small target detection Bottom reverberation suppressio Reverberation statistics characteristic Blind Source Separated

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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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Sparse Reconstruction Of Equivalence Classes Of Moving targets Using Single-Channel Synthetic Aperture Radar

Sparse Reconstruction Of Equivalence Classes Of Moving Targe...

引用

IEEE International conference on Acoustics, Speech and signal processing

作者： Jake Gunther Josh Hunsaker Hyrum Anderson Todd Moon Electrical & Computer Engineering Utah State University Logan UT 84322-4120 Sandia National Laboratory Data Analysis and Data Exploitation

ISBN: (纸本)9781479928941

Simultaneously estimating position and velocity of moving targets using only phase information from single-channel SAR data is impossible. This paper defines classes of equivalent target motion and solves the GMTI problem up to membership in an equivalence class using single-channel SAR phase data. We present a definitions for endo- and exo-clutter that is consistent with the equivalence classes, and show that most target motion can be detected, i.e. the set of endo-clutter targets is very small. We exploit the sparsity of moving targets in the scene to develop an algorithm to resolve target motion up to membership in an equivalence class, and demonstrate the effectiveness of the proposed technique using simulated data.

关键词： Equivalence classes Synthetic aperture radar targets single-channel Moving

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Detection, parametric imaging and classification of very small marine targets emerged in heavy sea clutter utilizing GPS-based Forward Scattering Radar

Detection, parametric imaging and classification of very sma...

引用

International conference on Acoustics, Speech, and signal processing (ICASSP)

作者： C. Kabakchiev V. Behar I. Garvanov D. Kabakchieva H. Rohling SU Sofia Bulgaria IICT-BAS Sofia Bulgaria ULSIT Sofia Bulgaria UWNE Sofia Bulgaria TU-HH Hamburg Germany

In this paper, we address a technique and related algorithms for precise detection, parametric imaging and classification of small marine targets in a harsh sensing environment attributed for heavy sea clutter via noncooperative processing of the GPS-based Forward Scatter Radar (FSR) data. In contrary to GPS L5 detection approach, the proposed technique utilizes civil GPS L1 signal formats in FSR exploiting GPS as a non-cooperative transmitter. In our previous studies it is shown that the use of the new power GPS signal L5, and the Forward Scattering effect providing a high SNR, at the detector input allows reliably to detect small air targets in conditions of the intense interference. In this paper we propose another approach, to enhance SNR, at the input of the detector in Forward Scattering Radar (FSR). The use of the effective filter (Local Variance Filter) for suppression of intensive sea clutter allows FSR reliably to detect small marine targets emerged in harsh sea clutter, but with GPS L1 signal, whose SNR is very small. At the classification level, the data mining approach is adopted, in which the target feature parameters are extracted from the preliminary filtered signals by utilizing the modified structure of a processor for target detection and parameter estimation in the time domain. Both, the decision tree-based and the neural network classifiers are featured and adapted for real-time implementation. The efficiency of the proposed technique is verified via analytical performance evaluations and experimental demonstrations.

关键词： Global Positioning System Radar scattering Radar signal to noise ratio Boats Classification algorithms

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A novel signal reconstructing method for radar targets

A novel signal reconstructing method for radar targets

引用

IEEE China Summit & International conference on signal and Information processing (ChinaSIP)

作者： Jia Duan Lei Zhang Yifeng Wu Mengdao Xing Min Wu National Key Laboratory of Radar Signal Processing Xidian University Xi'an P.R. China Xidian University Xian Shaanxi CN

In this paper, a novel signal reconstructing method for radar targets is proposed based on the attributed scattering center model. By extracting the attributed parameters, the large amount of target data can be represented by small amounts of attributed parameters. In this way, the data amount has been compressed sharply, which releases the computer memory for storage. After extraction, a target discriminating method is presented by applying a CFAR threshold to the energy of extracted attributed scattering centers, by which, weak distributed scattering centers with relatively high energy in total can be discriminated from noise under low SNRs. Experimental results validate the effectiveness of the signal reconstructing capability of the proposal.

关键词： Scattering Image reconstruction Radar imaging signal reconstruction Noise Parameter estimation

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A DSP-based video processing system for infrared small targets detection

A DSP-based video processing system for infrared small targe...

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International conference on Systems and Informatics (ICSAI)

作者： Yinan Cao Yan Zhou Xinwei Wang Songtao Fan Jun He Institute of Semiconductors Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781479954599

A DSP based system is proposed to detect infrared small targets in thermal imaging. The core of the system is TMS320DM6467T, in which an ARM9 and a C64+ DSP are integrated. The system includes a video capture module, a video process module and a video output module. To detect small targets in the video, an algorithm based on maximum between-class variance method in wavelet domain is proposed. Video stream data is obtained by a thermal imager, and then processed in proposed system. Experiment shows that the system is capable of target detection for thermal imaging.

关键词： Streaming media Digital signal processing Gray-scale Object detection Image segmentation Random access memory

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CONSTRUCTION OF DISCRIMINATIVE KERNELS FROM KNOWN AND UNKNOWN NON-targets FOR PLDA-SVM SCORING

CONSTRUCTION OF DISCRIMINATIVE KERNELS FROM KNOWN AND UNKNOW...

引用

IEEE International conference on Acoustics, Speech and signal processing

作者： Wei Rao Man-Wai Mak Dept. of Electronic and Information Engineering The Hong Kong Polytechnic University Hong Kong SAR China

ISBN: (纸本)9781479928941

Conventional PLDA scoring in i-vector speaker verification involves the i-vectors of target speakers and claimants only. We have previously demonstrated that better performance can be achieved by incorporating the information of background speakers in the scoring process via speaker-dependent SVMs. This is achieved by defining a PLDA score space with dimension equal to the number of training i-vectors for each target speaker. The new protocol in NIST 2012 SRE permits systems to use the information of other target-speakers (called known non-targets) in each verification trial. In this paper, we exploit this new protocol to enhance the performance of PLDA-SVM scoring by using the score vectors of both known and unknown non-targets as the impostor class data to train the speaker-dependent SVMs. Because some target speakers have one enrollment utterance only, which results in severe imbalance in the speaker- and impostor-class data for SVM training. This paper shows that if the enrollment utterance is sufficiently long, a number of target-speaker i- vectors can be generated by an utterance partitioning and resampling ii- technique, resulting in much better scoring SVMs. Results on NIST 2012 SRE demonstrate the advantages of pooling the known and unknown non-targets for training the SVMs and that the resampling techniques can help the SVM training algorithm to find better decision boundaries for those speakers with only a small number of enrollment utterances.

关键词： Loudspeakers Scoring Scoring Unknown speaker-dependent Support Vector Network Series Relay NIST Functional training

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Dual-sided subspace mappings for main-beam multi-target super-resolution in clutter and interference

Dual-sided subspace mappings for main-beam multi-target supe...

引用

IEEE National conference on Radar

作者： Manuel F. Fernández Kai-Bor Yu Independent Researcher Syracuse NY USA Independent Consultant Lake Forest CA USA

The need for localizing multiple main-beam targets in the presence of interference, clutter and jammers arises in scenarios such as: air defense, where a radar detection may correspond to one or multiple targets (e.g., a missile launched from an airborne platform); ballistic missile defense, where the incoming missile complex involves a large number of objects; cruise missile defense for low angle target tracking in multipath; etc. This paper presents a super-resolution approach for the sub-beamwidth localization of multiple main-beam targets in the presence of clutter and interference, doing so with a single snapshot of sensor array data while placing nulls at specified locations. Such process first maps array data into compact subspaces containing the information of interest (e.g., a cluster of receive beams with imbedded nulls). Super-resolution is then achieved via small-matrix operations on the subspace data. The ensuing result is a mapping of array data into a compressed “information domain,” yielding an effective, practical Sensor-to-Information process that is more accurate, robust and versatile than current super-resolution methods.

关键词： Arrays Clutter signal resolution Noise Vectors Array signal processing

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Behavior Subtraction applied to radar

Behavior Subtraction applied to radar

引用

IEEE International conference on Radar

作者： W.L. van Rossum M. Caro Cuenca Radar Technology TNO The Hague The Netherlands

An algorithm developed for optical images has been applied to radar data. The algorithm, Behavior Subtraction, is based on capturing the dynamics of a scene and detecting anomalous behavior. The radar application is the detection of small surface targets at sea. The sea surface yields the expected stable background dynamics, while a surface target will change the local dynamics due to its own motion. The results of the new algorithm have been compared with the more traditional STAP algorithm.

关键词： Radar imaging Sea surface Training Dynamics Training data signal processing algorithms

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A Novel Uplink data Transmission Scheme For small Packets In Massive MIMO System

A Novel Uplink Data Transmission Scheme For Small Packets In...

引用

IEEE/CIC International conference on Communications in China

作者： Ronggui Xie Huarui Yin Zhengdao Wang Xiaohui Chen Department of Electronic Engineering and Information Science University of Science and Technology of China Department of Electrical and Computer Engineering Iowa State University

ISBN: (纸本)9781479941452

Intelligent terminals often produce a large number of data packets of small lengths. For these packets, it is inefficient to follow the conventional medium access control (MAC) protocols because they lead to poor utilization of service resources. We propose a novel multiple access scheme that targets massive multiple-input multiple-output (MIMO) systems based on compressive sensing (CS). We employ block precoding in the time domain to enable the simultaneous transmissions of many users, which could be even more than the number of receive antennas at the base station. We develop a block-sparse system model and adopt the block orthogonal matching pursuit (BOMP) algorithm to recover the transmitted signals. Conditions for data recovery guarantees are identified and numerical results demonstrate that our scheme is efficient for uplink small packet transmission.

关键词： MIMO communication compressed sensing BOMP algorithm block orthogonal matching pursuit algorithm block precoding block-sparse system model compressive sensing intelligent terminals massive MIMO system massive multiple-input multiple-output systems novel multiple access scheme novel uplink data transmission scheme time domain Antennas data communication MIMO signal processing signal processing algorithms Throughput Uplink

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