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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251-260 订阅

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A robust motion compensation algorithm for ISAR imaging of sea-surface targets by Airborne Radar

A robust motion compensation algorithm for ISAR imaging of s...

引用

IEEE International conference on signal processing, Computing and Control (ISPCC)

作者： B. B. Mohapatra Vinod K Jaisaval Suchith Rajagopal Electronics & Radar Development Establishment DRDO Bangalore India

Motion compensation is the most critical part of Inverse Synthetic Aperture Radar (ISAR) processing in Airborne Radars. For an X-band Airborne Radar where resolution requirement is not sub-metric, Range-Doppler algorithm is the preferred choice to generate ISAR images due to small rotation angle requirement. In addition when both the radar platform and target are expected to move at nearly steady course and speed within the image formation interval, the use of highly sophisticated motion compensation algorithms is not desirable. This paper presents a robust and computationally efficient algorithm for translational motion compensation based on batch profile correlation. The algorithm is robust to background noise and target scintillation effects. It removes the problem of error accumulation inherent in peak-tracking method and avoids limitation of range-shift in integer steps. The effectiveness of the approach is verified by applying the algorithm to simulated ISAR data as well as actual ISAR data collected by an X-band airborne radar. The ISAR data simulation and processing are carried out using MATLAB. Different noise levels and target amplitude fluctuation are added to the simulated ISAR data to test the robustness of the algorithm.

关键词： Radar imaging Motion compensation Correlation Airborne radar Robustness Imaging

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Mixing Decoded Cursor Velocity and Position from an Offline Kalman Filter Improves Cursor Control in People with Tetraplegia

Mixing Decoded Cursor Velocity and Position from an Offline ...

引用

6th International IEEE EMBS conference on Neural Engineering (NER)

作者： Homer, Mark L. Harrison, Matthew T. Black, Michael J. Perge, Janos A. Cash, Sydney S. Friehs, Gerhard Hochberg, Leigh R. Brown Univ Biomed Engn Providence RI 02912 USA Brown Univ Div Appl Math Providence RI 02912 USA Max Planck Inst Intelligence Syst Tubingen Germany Brown Univ Dept Comp Sci Providence RI 02912 USA Ctr Neurorestorat & Neurotechnol Rehabil Res & Dev Serv Dept Vet Affairs Med Ctr Providence RI 02908 USA Brown Univ Sch Engn Providence RI 02912 USA Harvard Med Sch Massachussets Gen Hosp Dept Neurol Boston MA 02114 USA Amer Med Ctr Nicosia Cyprus

ISBN: (纸本)9781467319690

Kalman filtering is a common method to decode neural signals from the motor cortex. In clinical research investigating the use of intracortical brain computer interfaces (iBCIs), the technique enabled people with tetraplegia to control assistive devices such as a computer or robotic arm directly from their neural activity. For reaching movements, the Kalman filter typically estimates the instantaneous endpoint velocity of the control device. Here, we analyzed attempted arm/hand movements by people with tetraplegia to control a cursor on a computer screen to reach several circular targets. A standard velocity Kalman filter is enhanced to additionally decode for the cursor's position. We then mix decoded velocity and position to generate cursor movement commands. We analyzed data, offline, from two participants across six sessions. Root mean squared error between the actual and estimated cursor trajectory improved by 12.2 +/- 10.5% (pairwise t-test, p < 0.05) as compared to a standard velocity Kalman filter. The findings suggest that simultaneously decoding for intended velocity and position and using them both to generate movement commands can improve the performance of iBCIs.

关键词： Kalman filters biomechanics biomedical electrodes brain-computer interfaces filtering theory mean square error methods medical disorders medical robotics medical signal processing motion control neurophysiology position control velocity control

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INTRODUCING THE MONASH VISION GROUP'S CORTICAL PROSTHESIS

INTRODUCING THE MONASH VISION GROUP'S CORTICAL PROSTHESIS

引用

IEEE International conference on Image processing

作者： Arthur James Lowery Monash Vision Group Department of Electrical and Computer Systems Engineering Monash University Wellington Road Clayton VIC3800 Australia

ISBN: (纸本)9781479923427

Monash Vision Group is developing a bionic eye based on implanting 7-11 small tiles into the visual cortex. Each tile has 43 active electrodes on its base, and a wirelessly powered electronic system to decode control signals and drive the electrodes with biphasic pulses. The tiles are fed with power and data using a common transmitting coil at the back of the patient's head. Sophisticated image processing, described in a companion paper, ensures that the user experiences maximum benefit from the small number of electrodes. This paper describes the progress in the first three years (2010-2012) of this four-year project.

关键词： Visual prosthesis bionic eye visual cortex cortical implant electrostimulation Bionic Eye Visual Prosthesis Electric Stimulation Visual Cortex Tile Sight Prosthesis CONTROL signal Electronic systems

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A Fast Coalescence-Avoiding JPDAF

A Fast Coalescence-Avoiding JPDAF

引用

conference on signal and data processing of small targets

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

ISBN: (纸本)9780819490711

In this paper we present a new algorithm for approximating the target-measurement association probabilities of the Joint Probabilistic data Association Filter (JPDAF). This algorithm is designed to robustify the JPDAF against track coalescence which can greatly degrade the performance of the JPDAF and other approximate algorithms. It is based on the works of Roecker and the JPDAF* of Blom and Bloem. We compare our new algorithm with the two it is based on, as well as the "cheap JPDAF" and the Set JPDAF, and show that it offers a significant improvement in computational complexity over the JPDAF*, and improvement in tracking error over the Roecker algorithm. We compare their performance with respect to the Mean Optimal Subpattern Assignment (MOSPA) statistic in scenarios involving several closely-spaced targets. A consistency comparison of the various algorithms considered is also presented.

关键词： Detection and tracking algorithms Target detection Monte Carlo methods Error analysis Algorithm development Computer simulations Statistical analysis Time metrology data processing signal processing

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Multi-targets Miss Distance Measurement using Sequential Range-Doppler Image

Multi-Targets Miss Distance Measurement using Sequential Ran...

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2012 IEEE 11th International conference on signal processing(ICSP 2012)

作者： Dingwei Feng Siliang Wu Guohua Wei School of Information and Electronics Beijing Institute of Technology

ISBN: (纸本)9781467321969

A new approach is described for combining a series of sequential range and Doppler data from single radar platform to perform multi-targets miss distance measurement (MTMDM). In MTMDM, the difference between targets is mainly in range domain, not velocity. This difference leads to resemblance or aliasing in time curves of multi-targets Doppler frequency. Moreover, the miss distance measurement (MDM) using only distance information has some limitations such as larger measurement errors in case of small miss distance. In the new approach, the information of range and Doppler frequency will be first extracted using the centroid estimation method from range-Doppler image. Then the extracted information will be jointly used for multi-targets data association, tracking as well as MDM. The data association and fusion of range and Doppler can distinguish multi-targets, and improve the accuracy of the MDM more effectively. The experimental results will prove the efficiency of the proposed method.

关键词： multi-targets miss distance measurement range-Doppler image data fusion

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H-PMHT for Correlated targets

H-PMHT for Correlated Targets

引用

conference on signal and data processing of small targets

作者： Davey, Samuel J. Wieneke, Monika Gordon, Neil J. Defence Science and Technology Organisation (Australia) Univ. of Bonn (Germany)

ISBN: (纸本)9780819490711

The Histogram Probabilistic Multi-Hypothesis Tracker (H-PMHT) is a parametric track-before-detect algorithm that has been shown to give good performance at a relatively low computation cost. Recent research has extended the algorithm to allow it to estimate the signature of targets in the sensor image. This paper shows how this approach can be adapted to address the problem of group target tracking where the motion of several targets is correlated. The group structure is treated as the target signature, resulting in a two-tiered estimator for the group bulk-state and group element relative position.

关键词： Image sensors Detection and tracking algorithms Sensors Motion models Expectation maximization algorithms Image processing Process modeling Statistical analysis Image segmentation Motion estimation

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small curvature particle flow for nonlinear filters

Small curvature particle flow for nonlinear filters

引用

conference on signal and data processing of small targets

作者： Daum, Fred Huang, Jim Raytheon Co Woburn MA USA

ISBN: (纸本)9780819490711

We derive seven new particle flow algorithms for nonlinear filters based on the small curvature condition inspired by fluid dynamics. We find it extremely interesting that this physically motivated condition generalizes two of our previous exact flow algorithms, namely incompressible flow and Gaussian flow. We derive a new algorithm to compute the inverse of the sum of two linear differential operators using a second homotopy, similar to Feynman's perturbation theory for quantum electrodynamics as well as Gromov's h-principle.

关键词： particle filter nonlinear filter particle flow Kalman filter extended Kalman filter

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Particle Filter Tracking for Long Range Radars

Particle Filter Tracking for Long Range Radars

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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)9780819490711

In this paper we present an approach for tracking in long range radar scenarios. We show that in these scenarios the extended Kalman filter is not desirable as it suffers from major consistency problems, and that particle filters may 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 and the Gaussian Mixture Sigma-Point Particle Filter are shown to avoid this diversity problem while producing consistent results.

关键词： Particles Particle filters Detection and tracking algorithms Radar Filtering (signal processing) Gaussian filters Digital filtering Expectation maximization algorithms Statistical analysis signal processing

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VNIR data processing of small (Human) targets

VNIR Data Processing of Small (Human) Targets

引用

conference on signal and data processing of small targets

作者： Rosario, Dalton USA Res Lab Adelphi MD 20783 USA

ISBN: (纸本)9780819490711

We demonstrate that human skin biometrics in the visible to near infrared (VNIR) regime can be used as reliable features in a multistage human target tracking algorithm suite. We collected outdoor VNIR hyperspectral data of human skin, consisting of two human subjects of different skin types in the Fitzpatrick Scale (Type I [Very Fair] and Type III [White to Olive]), standing side by side at seven ranges (50 ft to 370 ft) in a suburban background. At some of these ranges, the subjects fall under the small target category. We propose a three-step approach: Step 1, reflectance retrieval;Step 2, exploitation of absorption wavelength line at 577 nanometers, due to oxygenated hemoglobin in blood near the surface of skin;and Step 3, matched filtering on candidate patches in the input imagery that successfully passed Step 2, using as input all of the available bands in a spectral average representation of human skin. Step-3 functionality is only applied to patches in the imagery showing evidence of human skin (Step 2 output). Regardless of the targets' kinematic states, the approach produced some excellent results locating the presence of human skin in the example dataset, yielding zero false alarms from potential confusers in the scene. The approach is expected to function as the focus of attention stage of a multistage algorithm suite for human target tracking.

关键词： small targets hyperspectral human skin detection

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Stochastic data Association in Multi-Target Filtering

Stochastic Data Association in Multi-Target Filtering

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conference on signal and data processing of small targets

作者： Coraluppi, Stefano Carthel, Craig Compunetix Inc Monroeville PA 15146 USA

ISBN: (纸本)9780819490711

Multi-target filtering for closely-spaced targets leads to degraded performance with respect to single-target filtering solutions, due to measurement provenance uncertainty. Soft data association approaches like the probabilistic data association filter (PDAF) suffer track coalescence. Conversely, hard data association approaches like multiple-hypothesis tracking (MHT) suffer track repulsion. We introduce the stochastic data association filter (SDAF) that utilizes the PDAF weights in a stochastic, hard data association update step. We find that the SDAF outperforms the PDAF, though it does not match the performance of the MHT solution. We compare as well to the recently-introduced equivalence-class MHT (ECMHT) that successfully counters the track repulsion effect. Simulation results are based on the steady-state form of the Ornstein-Uhlenbeck process, allowing for lengthy stochastic realizations with closely-spaced targets.

关键词： Multi-target filtering track coalescence track repulsion probabilistic data association filter (PDAF) stochastic data association filter (SDAF) multiple-hypothesis tracking (MHT) equivalence-class MHT (ECMHT)

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