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检索条件"任意字段=4th IEEE Sensor Array and Multichannel Signal Processing Workshop"

共 931 条记录，以下是561-570 订阅

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thE HYBRID CRAMER-RAO BOUND AND thE GENERALIZED GAUSSIAN LINEAR ESTIMATION PROBLEM

THE HYBRID CRAMER-RAO BOUND AND THE GENERALIZED GAUSSIAN LIN...

引用

2008 ieee sensor array and multichannel signal processing workshop

作者： Y. Noam H. Messer School of Electrical Engineering Tel-Aviv University Israel

this paper explores the Hybrid Cramer-Rao Lower-bound (HCRLB) for a Gaussian generalized linear estimation problem in which some of the unknown parameters are deterministic while the other are random. In general, the HCRLB on the non-Bayesian parameters is not asymptotically tight. However, we show that for the generalized Gaussian linear estimation problem, the HCRLB of the deterministic parameters coincides with the CRLB, so it is an asymptotically tight bound. In addition, we show that the ML/MAP estimator [1] is asymptotically efficient for the non-Bayesian parameters while providing optimal estimate of the Bayesian parameters. the results are demonstrated on a signal processing example. It is shown the Hybrid estimation can increase spectral resolution if some prior knowledge is available only on a subset of the parameters.

关键词： Maximum likelihood estimation Estimation Bayesian methods Vectors Radio access networks Joints signal processing

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MIMO radar signal processing for distributed phased arrays

MIMO radar signal processing for distributed phased arrays

引用

ieee International workshop on Computational Advances in Multi-sensor Adaptive processing (CAMSAP)

作者： Daniel R. Fuhrmann Department of Electrical and Computer Engineering Michigan Technological University Houghton MI USA

We explore transmit signaling and receive signal processing strategies for a notional MIMO radar system consisting of widely distributed phased arrays. the assumptions are that within a phased array, there is a fixed rigid geometry and perfect phase synchronization, and there is a single look at the target. In constrast, between phased arrays there is imperfect phase synchronization and multiple views of the target. the relative advantages and disadvantages of coherent and orthogonal signaling in such a model are explored through simulation.

关键词： Phased arrays MIMO radar array signal processing Synchronization Estimation MIMO

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An Anti-jamming Method of ISAR Imaging with FDA-MIMO Radar

An Anti-jamming Method of ISAR Imaging with FDA-MIMO Radar

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sensor array and multichannel signal processing workshop

作者： Guangming Li Qun Zhang Ying Luo Kaiming Li Linghua Su Rui Li Graduate college Air Force Enginnering University Xi'an China Information and Navigation college Air Force Enginnering University Xi'an China

In recent years, the frequency diverse array (FDA) radar has attracted much attention due to its range-angle dependent beam-pattern. And multiple input multiple output (MIMO) radar has been widely investigated with the advantage of transmit waveform diversity. In this paper, a FDA-MIMO Inverse Synthetic Aperture Radar (ISAR) is proposed to achieve anti-jamming of ISAR imaging. LFM (Linear Frequency Modulated) and SFCS (Stepped-Frequency Chirp signal) signals are transmitted to jammer and targets respectively, and the received signals are matched filtering by the signal transmitted to the targets. So the jamming signal can't matched with the reference signal, the well anti-jamming effect can be obtained. the performance of the proposed method is evaluated by the simulation results.

关键词： Jamming Radar imaging array signal processing Imaging Radar signal processing Frequency modulation

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Detection in analog sensor networks with a large scale antenna fusion center

Detection in analog sensor networks with a large scale anten...

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sensor array and multichannel signal processing workshop

作者： Feng Jiang Jie Chen A. Lee Swindlehurst Center for Pervasive Communications and Computing University of California at Irvine Irvine CA USA

We consider the distributed detection of a zero-mean Gaussian signal in an analog wireless sensor network with a fusion center (FC) configured with a large number of antennas. the transmission gains of the sensor nodes are optimized by minimizing the ratio of the log probability of detection (PD) and log probability of false alarm (PFA). We show that the problem is convex with respect to the squared norm of the transmission gains, and that a closed-form solution can be found using the Karush-Kuhn-Tucker conditions. Our results indicate that a constant PD can be maintained with decreasing sensor transmit gain provided that the number of antennas increases at the same rate. this is contrasted with the case of a singleantenna FC, where PD is monotonically decreasing with transmit gain. On the other hand, we show that when the transmit power is high, the single- and multi-antenna FC both asymptotically achieve the same PD upper bound.

关键词： Wireless sensor networks Upper bound Wireless communication Transmitting antennas Antenna measurements Fading

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Hybrid Particle Filtering Based on an Elitist Resampling Scheme

Hybrid Particle Filtering Based on an Elitist Resampling Sch...

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sensor array and multichannel signal processing workshop

作者： Mhd Modar Halimeh Christian Huemmer Andreas Brendel Walter Kellermann Multimedia Communications and Signal Processing Friedrich-Alexander-Universität Erlangen-Nürnberg Erlangen Germany

In this paper, the elitist resampling particle filter (ERPF) is introduced. the ERPF is an approach to combine generic particle filters, i.e., the SIS and SIR particle filter, based on an evolutionary selection of particles, which introduces a longterm memory to the selected group of the particles. thereby, the ERPF aims at fusing the advantages, e.g., robustness and computational efficiency, and mitigating the drawbacks of each filter, e.g., degeneracy and sample impoverishment. Two variants of the ERPF are presented in this paper: the discrete ERPF (DERPF) and the continuous ERPF (CERPF), which to the authors' knowledge represent new forms of particle filters. the two proposed hybrids are compared to the corresponding original filters using two well-established benchmark models to illustrate that the evolutionary combinations provide a better estimation accuracy and exhibit an increased robustness against outliers.

关键词： Estimation Particle filters Robustness Sociology Statistics array signal processing

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4th workshop on Real-World Wireless sensor Networks, REALWSN 2010

4th Workshop on Real-World Wireless Sensor Networks, REALWSN...

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4th workshop on Real-World Wireless sensor Networks, REALWSN 2010

ISBN: (纸本)9783642175190

the proceedings contain 26 papers. the special focus in this conference is on Real-World Wireless sensor Networks. the topics include: Evaluation of an electronically switched directional antenna for real-world low-power wireless networks;implementation and evaluation of combined positioning and communication;SPIDA: A direction-finding antenna for wireless sensor networks;testing selective transmission with low power listening;An experimental study on ieee 802.15.4 multichannel transmission to improve RSSI–Based service performance;multicasting enabled routing protocol optimized for wireless sensor networks;GINSENG - Performance control in wireless sensor networks;lynxNet: Wild animal monitoring using sensor networks;demo abstract: Bridging the Gap between simulated sensor nodes and the real world;TigerCENSE: Wireless image sensor network to monitor tiger movement;a mote-in-the-loop approach for exploring communication strategies for sensor networks;the deployment of TikiriDB for monitoring palm sap production;cooperative virtual memory for sensor nodes;ginConf: A configuration and execution interface for wireless sensor network in industrial context;ediMote: A flexible sensor node prototyping and profiling tool;Virtual sensor WPAN on demand;TikiriAC: Node-level equally distributed access control for shared sensor networks;Motes in the jungle: Lessons learned from a short-term WSN deployment in the Ecuador cloud forest;deploying wireless sensor networking technology in a rescue team context;visibility levels: Managing the tradeoff between visibility and resource consumption;Flexible online energy accounting in tinyOS;TikiriDev: A UNIX-Like device abstraction for contiki;location based wireless sensor services in life science automation;hallway monitoring: Distributed data processing with wireless sensor networks.

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Robust Adaptive Beamforming signal Techniques for Drone Surveillance

Robust Adaptive Beamforming Signal Techniques for Drone Surv...

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sensor array and multichannel signal processing workshop

作者： Shangang Fan Jiangbo Liu Mengqian Tian Hao Huang Fei Dai Lie Yang Guan Gui NJUPT College of Telecommunication and Information Engineering Nanjing China UESTC School of Electronic Engineering Chengdu China

Drone surveillance poses a big technical challenge in the signal beamforming due to the drones' small size and low flying speed at low altitude collisions and etc. In a drone surveillance system, robust adaptive beamforming is required to identify suspicious targets. However, interference motion and array steering vector (ASV) mismatch problems often occurs in the situation of the antenna platform motion or propagation channel variability. To solve these problems, we propose a robust adaptive beamforming algorithms, which can broaden interference nulls. Specifically, by introducing a norm constraint, the proposed algorithm produces a broad trough at the direction of interference and adopts an idea of worst case performance optimization to robustly against the ASV mismatch. Simulation results demonstrate the validity of the proposed algorithm in terms of both output beampattern and signal-to-interference-plus-noise ratio (SINR).

关键词： Interference Covariance matrices array signal processing Robustness signal processing algorithms signal to noise ratio Antenna arrays

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Comparison of Sparse arrays From Viewpoint of Coarray Stability and Robustness

Comparison of Sparse Arrays From Viewpoint of Coarray Stabil...

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sensor array and multichannel signal processing workshop

作者： Chun-Lin Liu P. P. Vaidyanathan Dept. of Electrical Engineering MC 136–93 California Institute of Technology Pasadena CA USA

Sparse arrays, such as minimum redundancy arrays (MRA), nested arrays, and coprime arrays, can resolve O(N 2 ), uncorrelated sources with N physical sensors, since they possess an O(N 2 ) -long uniform segment in the difference coarray, which is defined as the differences between sensor locations. Empirically, this O(N 2 ), property is susceptible to sensor failures. On the other hand, uniform linear arrays (ULA) are known to be robust, but they possess only O(N) elements in the difference coarray. this paper compares the size and the robustness of the difference coarray for a wide variety of array geometries. It is observed from numerical examples that, for a fixed N, increasing the size of the difference coarray typically makes it less robust to faulty sensors. Furthermore, it is noticed from examples that given two arrays with the same N and the same difference coarray, one could be much more robust than the other.

关键词： sensor arrays Robustness array signal processing Redundancy Geometry Conferences

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Covariance estimation in time varying ARMA processes

Covariance estimation in time varying ARMA processes

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sensor array and multichannel signal processing workshop

作者： Ami Wiesel Amir Globerson Hebrew University of Jerusalem Israel

We consider large scale covariance estimation using a small number of samples in applications where there is a natural ordering between the random variables. the two classical approaches to this problem rely on banded covariance and banded inverse covariance structures, corresponding to time varying moving average (MA) and autoregressive (AR) models, respectively. Motivated by this analogy to spectral estimation and the well known modeling power of autoregressive moving average (ARMA) processes, we propose a novel time varying ARMA covariance structure. Similarly to known results in the context of AR and MA, we address the completion of an ARMA covariance matrix from its main band, and its estimation based on random samples. Finally, we examine the advantages of our proposed methods using numerical experiments.

关键词： Covariance matrix Estimation Autoregressive processes Vectors Mathematical model signal processing Equations

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Power minimization in the multiple stream MIMO Broadcast Channel with imperfect CSI

Power minimization in the multiple stream MIMO Broadcast Cha...

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sensor array and multichannel signal processing workshop

作者： José P. González-Coma Michael Joham Paula M. Castro Luis Castedo Department of Electronics and Systems University of A Coruña Spain Technische Universitat Munchen Munchen Bayern DE Universidade da Coruna A Coruna Galicia ES

We address the design of linear precoders and receivers in a MIMO Broadcast Channel (BC) with perfect Channel State Information (CSI) at reception but partial CSI at the transmitter. Our aim is to minimize the transmit power subject to per-user rate constraints when multiple streams of data are sent to each user. We develop a gradient-projection algorithm to convert the per-user constraints into per-stream constraints. the MIMO BC linear precoders and receivers that minimize the transmit power are then obtained with an alternating optimization algorithm.

关键词： MIMO Optimization Equalizers signal processing algorithms Conferences Minimization

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