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检索条件"任意字段=2nd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing"

共 109 条记录，以下是61-70 订阅

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Performance of TOA and FOA-based Localization for Cospas-Sarsat Search and Rescue Signals

Performance of TOA and FOA-based Localization for Cospas-Sar...

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5th ieee international workshop on computational advances in multi-sensor adaptive processing (CAMSAP)

作者： Nicolau, Victor Bissoli Coulon, Martial Gregoire, Yoan Calmettes, Thibaud Tourneret, Jean-Yves Univ Toulouse INP ENSEEIHT IRIT 2 Rue Charles Camichel F-31071 Toulouse 7 France TESA F-31000 Toulouse France CNES F-31401 Toulouse France Thales Alenia Space F-31037 Toulouse 1 France

ISBN: (纸本)9781467331463;9781467331449

This work studies the performance of position estimation for distress beacons using time of arrival and frequency of arrival measurements. The analysis is conducted for emergency signals modeled as pulses with sigmoidal transitions. This model has shown interesting properties for Cospas-Sarsat search and rescue signals. The modified Cramer-Rao bounds of the symbol width, time of arrival, frequency of arrival, and position of this model are presented. Simulations conducted with realistic signals indicate good agreement between these bounds and the mean square errors of the estimated parameters.

关键词： Time of arrival

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Particle Filtering with Progressive Gaussian Approximations to the Optimal Importance Density

Particle Filtering with Progressive Gaussian Approximations ...

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5th ieee international workshop on computational advances in multi-sensor adaptive processing (CAMSAP)

作者： Bunch, Pete Godsill, Simon Univ Cambridge Dept Engn Signal Proc & Commun Lab Cambridge CB2 1PZ England

ISBN: (纸本)9781467331463;9781467331449

A new algorithm, the progressive proposal particle filter, is introduced. The performance of a standard particle filter is highly dependent on the choice of importance density used to propagate the particles through time. The conditional posterior state density is the optimal choice, but this can rarely be calculated analytically or sampled from exactly. Practical particle filters rely on forming approximations to the optimal importance density, frequently using Gaussian distributions, but these are not always effective in highly nonlinear models. The progressive proposal method introduces the effect of each observation gradually and incrementally modifies the particle states so as to achieve an improved approximation to the optimal importance distribution.

关键词： Particle filters Gaussian approximation Gaussian distribution Optimal

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Iterative root-MUSIC algorithm for DOA estimation

Iterative root-MUSIC algorithm for DOA estimation

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5th ieee international workshop on computational advances in multi-sensor adaptive processing (CAMSAP)

作者： Shaghaghi, Mahdi Vorobyov, Sergiy A. Univ Alberta Dept Elect & Comp Engn Edmonton AB T6G 2V4 Canada Aalto Univ Sch Elect Engn FI-00076 Espoo Finland

ISBN: (纸本)9781467331463;9781467331449

This paper introduces a new high-resolution subspace-based algorithm for direction-of-arrival estimation. The proposed method improves the quality of the estimation especially in the case of small sample size by considering the structure of the sample covariance matrix. The key idea is to identify undesirable terms in the sample covariance matrix which cause perturbations in the estimation of the signal and noise subspaces. These terms are then diminished in an iterative manner. The proposed method is studied by investigating the mean squared error, the detection probability, and the mean squared error in case of successful detection. It is shown that the new method outperforms the conventional methods.

关键词： Direction of arrival estimation sample covariance Sample Size Mean square error Iterative perturbation

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multi-Relay Network Design Using Power-Normalized SNR

Multi-Relay Network Design Using Power-Normalized SNR

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5th ieee international workshop on computational advances in multi-sensor adaptive processing (CAMSAP)

作者： Hao, Yichen Jing, Yindi ShahbazPanahi, Shahram Univ Alberta Dept Elect & Comp Engn Edmonton AB T6G 2M7 Canada

ISBN: (纸本)9781467331463;9781467331449

In this paper, we adopt a novel efficiency measure, the power-normalized SNR (PN-SNR), in the design of multi-relay networks with an individual power constraint for each relay. We formulate the PN-SNR maximization problem with a received SNR constraint to maintain the quality of service (QoS) and propose a low complexity algorithm for a suboptimal solution. The average PN-SNR and average throughput of the proposed design are simulated and compared with existing designs. We also simulate the probability of no transmission with the proposed design for an arbitrary SNR level. We observe that the proposed design is more power efficient than existing ones with comparable performance in average throughput. When the transmitter power is moderate, with higher QoS constraint, the probability of no transmission gets higher;the average throughput decreases, but the PN-SNR of the network increases.

关键词： signal to noise ratios Supernova remnants Transmitter power Quality of service Relay networks Individual Power Network design Throughput relay

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Root-MUSIC Based Source Localization Using Transmit Array Interpolation in MIMO Radar With Arbitrary Planar Arrays

Root-MUSIC Based Source Localization Using Transmit Array In...

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5th ieee international workshop on computational advances in multi-sensor adaptive processing (CAMSAP)

作者： Hassanien, Aboulnasr Vorobyov, Sergiy A. Yoon, Yeo-Sun Park, Joon-Young Univ Alberta Dept ECE Edmonton AB T6G 2V4 Canada Aalto Univ Dept Signal Proc & Acoust Espoo Finland Samsung Thales Co Ltd Software Grp Yongin 449885 South Korea

ISBN: (纸本)9781467331463;9781467331449

We consider the problem of target localization in MIMO radar with arbitrary planar arrays. A method for mapping a two-dimensional (2D) arbitrary transmit array into a uniform rectangular array or an L-shaped array with uniform element displacement is developed. The uniform structure of the mapped array enables applying the computationally efficient 2D root-MUSIC algorithm for estimating the elevation and azimuth parameters of the targets. The transmit array interpolation is achieved by properly designing the mapping matrix via solving a minmax convex optimization problem. We show that there is a tradeoff between the mapping accuracy within a certain desired 2D spatial sector and the sidelobe levels. The performance of the root-MUSIC for the mapped transmit array is shown to achieve the performance of the root-MUSIC associated with a perfect uniform array of the same shape as the mapped one. Simulation examples are used to validate the effectiveness of the proposed method.

关键词： Arbitrary arrays array interpolation direction finding MIMO radar root-MUSIC

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Aperture varying autoregressive covariance modeling for 2D oversampled receive arrays

Aperture varying autoregressive covariance modeling for 2D o...

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2013 5th ieee international workshop on computational advances in multi-sensor adaptive processing, CAMSAP 2013

作者： Abramovich, Yuri I. Antonio, Geoffrey San WR Systems Fairfax VA 22030 United States US Naval Research Laboratory Washington DC 20375 United States

ISBN: (纸本)9781467331463

Recently it has been proposed that two-dimensional (2D) oversampled received arrays could be used to provide signal-to-external noise ratio (SENR) gains for over-the-horizon radar applications which are strongly externally noise limited. These array configurations can be used to exploit superdirective adaptive beamforming techniques. A key element of the superdirective adaptive beamforming process is the estimation of the array spatial noise covariance matrix. In this paper we propose a parametric covariance modeling technique called aperture varying autoregressive (AVAR) covariance modeling that captures the 2D spatial correlation structure of high-frequency (HF) background noise sampled by an oversampled 2D receive array. The use of this covariance modeling technique can significantly reduce the computational requirements for the inversion of large spatial covariance matrices. Additional gains are achieved via reduced sample support requirements for an N-element 2D receive array. In this paper we introduce 2D aperture varying autoregressive models AVAR(m,l) that are spatially non-stationary generalizations of traditional autoregressive AR(m) or AR (m,l) techniques. While traditional AR techniques model covariance structure as toeplitz or toeplitz-block-toeplitz, these new AVAR models enforce a banded or doubly banded inverse covariance structure which is more general. The introduced AVAR methods are closely coupled to the oversampled array architecture which in the presence of nearly homogeneous external noise exhibits spatial correlation most strongly amongst closely spaced elements. Therefore the use of these AVAR methods effectively restricts the adaptive beamforming to gains achievable through superdirective beamforming. © 2013 ieee.

关键词： Beamforming

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Speckle reducing diffusion for ultrasound image enhancement using the structural similarity image measure

Speckle reducing diffusion for ultrasound image enhancement ...

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ieee international workshop on computational advances in multi-sensor adaptive processing (CAMSAP)

作者： Scott T. Acton C.L. Brown Dept. of Electrical & Computer Engineering Dept. of Biomedical Engineering University of Virginia Charlottesville Virginia USA

An adaptive approach to enhancing images obtained from an array of ultrasonic transducer elements is proposed and evaluated. The basic algorithm is driven by a system of partial differential equations that 1) reduce speckle by way of the instantaneous (local) coefficient of variation and 2) force congruence with an anatomical model using a well-known perceptual quality metric. A differential form of the quality metric, the structural similarity image measure (SSIM), is derived and applied. This update mechanism registers the image data to the model, thus solving segmentation simultaneously with enhancement. The algorithm, called SSIM diffusion, is tested on a needle placement application in phlebotomy in which delineation of a vessel boundary is required. A group of images obtained from a portable C-scan ultrasonic sensor is used to evaluate the enhancement and segmentation algorithm. Comparisons to a standard speckle reducing diffusion algorithm show that the modelAbased SSIM diffusion superior enhancement with a 67% increase in measurable image quality over the original.

关键词： Speckle Ultrasonic imaging computational modeling Data models Image quality Conferences Adaptation models

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2007 2nd ieee international workshop on computational advances in multi-sensor adaptive processing, CAMPSAP

2007 2nd IEEE International Workshop on Computational Advanc...

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2007 2nd ieee international workshop on computational advances in multi-sensor adaptive processing, CAMPSAP

ISBN: (纸本)9781424417148

The proceedings contain 77 papers. The topics discussed include: semi-supervised life-long learning with application to sensing;hybrid adaptive receiver processing for multistatic radar;adaptive sensing of dynamic target state in heavy sea clutter;multi-channel parametric estimator fast block matrix inverses;particle filtering-based target tracking in binary sensor networks using adaptive thresholds;on adaptive sensing of complex communication channels;a Bayesian estimation bound based on the optimal bias function;sparse Bayesian estimation of superimposed signal parameters;a lower bound for sequential estimators;experimental studies on direction finding via blind beamforming;reduction of spatial sampling requirement in sound-based synthesis;fast low-rank approximation for covariance matrices;a collaborative training algorithm for multi-sensor adaptive processing;and compress-and-forward relaying over parallel Gaussian channels.

关键词： Target tracking

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Aperture varying autoregressive covariance modeling for 2D oversampled receive arrays

Aperture varying autoregressive covariance modeling for 2D o...

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ieee international workshop on computational advances in multi-sensor adaptive processing (CAMSAP)

作者： Yuri I. Abramovich Geoffrey San Antonio WR Systems Fairfax VA USA

关键词： Covariance matrices Noise Array signal processing Adaptation models computational modeling adaptive arrays Approximation methods

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Nonnegative matrix factorization with regularization and sparsity-enforcing terms

Nonnegative matrix factorization with regularization and spa...

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2011 4th ieee international workshop on computational advances in multi-sensor adaptive processing, CAMSAP 2011

作者： Lantéri, Henri Theys, Céline Richard, Cédric Laboratoire H.Fizeau UMR 6525 Universite de Nice-Sophia Antipolis 06108 Cedex 2 France

ISBN: (纸本)9781457721052

The aim of this paper is to present several multiplicative algorithms for nonnegative matrix factorization. We show how to obtain such algorithms in the case where non-negativity and flux conservation constraints are imposed, and how to regularize such problems by introducing smoothness or sparsity properties. Application to hyperspectral imagery is finally considered. © 2011 ieee.

关键词： Matrix algebra

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