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检索条件"任意字段=18th Conference on Signal and Data Processing of Small Targets"

共 390 条记录，以下是31-40 订阅

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Radar detection of multiple moving targets in clutter using time-frequency-radon transform

Radar detection of multiple moving targets in clutter using ...

引用

14th conference on signal and data processing of small targets

作者： Chen, VC USN Res Lab Div Radar Washington DC 20375 USA

ISBN: (纸本)0819444782

In this paper, we analyze features of radar returns from moving targets, introduce the basic concept of time-frequency-Radon transforms, describe the Radon transform for line feature detection, discuss their applications to detection of multiple moving targets in clutter, and demonstrate two examples of moving target detection using simulated radar data.

关键词： time-frequency transform Radon transform moving targets multiple targets

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Parameter estimation for multistatic active sonar using extended fixed points 18

Parameter estimation for multistatic active sonar using exte...

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18th International conference on Information Fusion (Fusion)

作者： Broetje, Martina Pikora, Kolja Fraunhofer FKIE Dept Sensor Data & Informat Fusion Wachtberg Germany Univ Kiel Fac Engn Digital Signal Proc & Syst Theory Kiel Germany Bundeswehr Tech Ctr Ships & Naval Weap Naval Technol & Res Res Dept Underwater Acoust & Marine Geophys Kiel Germany

ISBN: (纸本)9780982443866

the main task of multistatic active sonar is the localisation and tracking of objects of interest (targets). therefore, a precise knowledge of the parameters of the multistatic scenario is mandatory. these are the positions of the acoustic sources, the times of transmission, as well as the position and heading of the own sonar sensor. Reflections from so called "fixed points" can be used to improve knowledge about these parameters. A fixed point can be a wreck or geographical feature (e.g. a small island) with known position. In general these fixed points consist of multiple scattering points, thus, the assumption of a point-like target is not fulfilled. In this paper we discuss the impact that an extension of the fixed point has on the estimation process and derive a method within the Kalman filter measurement update to incorporate knowledge about the extension in the estimation approach. Results will be discussed for simulated data.

关键词： Sonar

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Target detection by distributed sensors: distributed sensor concept-DISCO for small target detection

Target detection by distributed sensors: distributed sensor ...

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20th conference on signal and data processing of small targets

作者： Rafailov, Michael K. QinetiQ NA Reston VA 20191 USA

ISBN: (纸本)9780819471604

Distributed Sensor Concept - DISCO was proposed [I] for multiplication of individual sensor capabilities through non-coherent cooperative target engagement. the signal processing technique for DISCO is Recursive Adaptive Frame Integration of Limited data - RAFIL technique [2] that was initially proposed as a way to improve the SNR [3], reduce data rate [4] and mitigate FPA noise for IR sensors [5]. In DISCO, the RAFIL technique is used in a segmented way, when constituencies of the technique are spatially and temporally separated between individual sensors. Each sensor provides to and receives data from other sensors in the network. In this paper efficiency of DISCO is discussed for acquisition, accurate handover and track correlation of small targets.

关键词： multiple sensor system distributed sensors distributed apertures accurate target detection frame integration data rate recursive processing double threshold

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Iterative Pre-Whitening Projection Statistics for Non-Homogeneous Clutters with Multiple targets

Iterative Pre-Whitening Projection Statistics for Non-Homoge...

引用

18th Asia-Pacific conference on Communications (APCC) - Green and Smart Communications for IT Innovation

作者： Park, Hyuck Kang, Jin Whan Kim, Sang-Hyo Samsung Thales R&D Ctr Yongin 449885 South Korea Sungkyunkwan Univ Coll Informat & Commun Engn Suwon 440746 South Korea

ISBN: (纸本)9781467347280

In this paper, we propose a modified iterative pre-whitening projection statistics (MIPPS) method for multi-target detection in non-homogeneous clutters. MIPPS determines and excludes non-homogeneous data samples by iteratively updating a pre-whitening matrix and performing the PS algorithm. Numerical results show that MIPPS improves the average detection probability of weak target when multiple targets with different signal intensities are mixed at low signal-to-clutter ratios.

关键词： clutter signal Intensity Object detection data sampling targets Iterative PROJECTION Projection

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REDUCING thE TRAINING SET USING SEMI-SUPERVISED SELF-TRAINING ALGORIthM FOR SEGMENTING thE LEFT VENTRICLE IN ULTRASOUND IMAGES

REDUCING THE TRAINING SET USING SEMI-SUPERVISED SELF-TRAININ...

引用

18th IEEE International conference on Image processing (ICIP)

作者： Nascimento, Jacinto C. Carneiro, Gustavo Inst Super Tecn Inst Sistemas & Robot P-1049001 Lisbon Portugal

ISBN: (纸本)9781457713033

Statistical pattern recognition models are one of the core research topics in the segmentation of the left ventricle of the heart from ultrasound data. the underlying statistical model usually relies on a complex model for the shape and appearance of the left ventricle whose parameters can be learned using a manually segmented data set. Unfortunately, this complex requires a large number of parameters that can be robustly learned only if the training set is sufficiently large. the difficulty in obtaining large training sets is currently a major roadblock for the further exploration of statistical models in medical image analysis. In this paper, we present a novel semi-supervised self-training model that reduces the need of large training sets for estimating the parameters of statistical models. this model is initially trained with a small set of manually segmented images, and for each new test sequence, the system re-estimates the model parameters incrementally without any further manual intervention. We show that state-of-the-art segmentation results can be achieved with training sets containing 50 annotated examples.

关键词： data models Image segmentation Manuals Robustness Training Ultrasonic imaging Vectors

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Detection of small target in IR image sequences using VSLMS

Detection of small target in IR image sequences using VSLMS

引用

16th conference on signal and data processing of small targets

作者： Ng, LN Ronda, V Lim, ET Nanyang Technol Univ Sch Elect & Elect Singapore Singapore

ISBN: (纸本)081945351X

A Vertical-Strip Least Mean Squared (VSLMS) algorithm is proposed to enhance the detection of small moving targets in IR image sequences. this algorithm is an improvement over the Two-Dimensional LMS (TDLMS), which is designed to detect small targets within highly correlated background of static images. this paper focuses on processing IR image sequences with different background features with layers of sky, sea and land clutter. the VSLMS uses multiple LMS modules and a different scanning method to process individual lines in the IR image sequences. Simulation results show successful enhancement of very small targets in an IR mage sequence.

关键词： VSLMS IR image sequences TDLMS

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Tracking of two closely spaced objects using monopulse measurements

Tracking of two closely spaced objects using monopulse measu...

引用

17th conference on signal and data processing of small targets

作者： Isaac, A Zhang, X Willett, P Bar-Shalom, Y Univ Connecticut Dept Elect & Comp Engn Storrs CT 06269 USA

ISBN: (纸本)0819459186

the ultimate goal of this paper is to track two closely spaced and unresolved targets using monopulse radar measurements, the quality of such tracking being a determinant of successful detection of target spawn. It explores statistical estimation techniques based on the maximum likelihood criterion and Gibbs sampling, and addresses concerns about the accuracy of the measurements delivered thereby. In particular, the Gibbs approach can deliver joint measurements (and the associated covariances) from both targets, and it is therefore natural to consider a joint filter. the ideas are compared, and amongst the various strategies discussed, a particle filter that operates directly on the monopulse measurements is especially promising.

关键词： Radar Filtering (signal processing) Detection and tracking algorithms Particle filters Target detection Particles signal processing Monte Carlo methods signal to noise ratio Statistical analysis

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TRACK BEFORE DETECT DOA TRACKING OF EXTENDED targets WIth MARKED POISSON POINT PROCESSES 18

TRACK BEFORE DETECT DOA TRACKING OF EXTENDED TARGETS WITH MA...

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18th International conference on Information Fusion (Fusion)

作者： Saucan, Augustin-Alexandra Chonavel, thierry Sinles, Christophe Le Caillec, Jean-Marc Inst Mines Telecom Telecom Bretagne CNRS LabSTICC UMR 6285 Technopole Brest Iroise CS 83818 F-29238 Brest 3 France

ISBN: (纸本)9780982443866

In this paper we propose a novel Track Before Detect (TBD) filter aimed at tracking multiple extended targets from phased-array observations. For extended targets, the source signal is angularly distributed, and hence we track the centroid Direction Of Arrival (DOA) of the target generated signal - called target signal. In this work we suppose known the shape and extent of the target-signal angular spread. Solutions based on extending the system state, to include the target signal, lead to higher-dimensional posteriors. We avoid an extended state by using a novel Marked Poisson Point Process (MPPP) model for the system, and accordingly, we derive the intensity/PHD filter that adaptively estimates target number and corresponding centroid DOAs. the source signals are interpreted as the mark of a target, and they are analytically integrated in the update formula of the filter. therefore, an efficient particle filter implementation is possible. Results on simulated data showcase the improved results of the proposed filter over state-of-the-art methods.

关键词： DOA tracking marked Poisson point process track before detect extended target DBSCAN

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Tracking with asynchronous multiple sensors

Tracking with asynchronous multiple sensors

引用

13th conference on signal and data processing of small targets

作者： Gray, JE McCabe, DH USN Ctr Surface Warfare Dahlgren Div Syst Res & Technol Dept Dahlgren VA 22448 USA

ISBN: (纸本)0819441872

Sensor data fusion has long been recognized as a means to improve target tracking. Common practice assumes that the sensors used are synchronous (i.e., perform the, same operation at the identical time), take measurements at the same time and have no communication delays between sensor platforms and the central processing center. Such assumptions are not valid in practice. this paper removes these assumptions when dealing with multisensor target tracking. In particular, it assumes that the sensors used can have different data rates and communication delays between local and central platforms. A new tracking algorithm using asynchronous sensors is proposed and derived in this paper.

关键词： Filtering (signal processing) Lithium Sensors Silicon Zinc Electronic filtering Lutetium data communications data processing signal processing

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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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