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检索条件"任意字段=2008 IEEE Sensor Array and Multichannel Signal Processing Workshop"

共 1267 条记录，以下是281-290 订阅

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Over-The-Air Identification of Coupled Nonlinear Distortion in a MIMO Radar 12

Over-The-Air Identification of Coupled Nonlinear Distortion ...

引用

ieee 12th sensor array and multichannel signal processing workshop (SAM)

作者： Kylin, Carl Eriksson, Thomas Silander, Anders McKelvey, Tomas Chalmers Univ Technol Dept Elect Engn Gothenburg Sweden Saab AB Radar Solut Gothenburg Sweden

ISBN: (纸本)9781665406338

Compensation for nonlinear distortion caused by power amplifiers being driven into compression is a field that has been extensively explored by a number of authors. More complex models describing the coupled nonlinear distortion that can occur in an active antenna array also exist. To identify these models most authors assume that the output of each power amplifier can be measured directly. For a system with many antennas over-theair identification might be favorable. The problem of identifying a system describing the joint effects of coupled nonlinear distortion over-the-air has been solved by other authors assuming model or setup simplifications. To tackle the problem with a more accurate model, an algorithm for identifying parameters of a Volterra series model describing coupled non-linear distortion in a digital radar is explored and illustrated with simulated data.

关键词： Power measurement MIMO radar Nonlinear distortion Power amplifiers signal processing algorithms Radar Data models

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Sparse Channel Estimation for IRS-Aided Systems Exploiting 2-D Sparse arrays 12

Sparse Channel Estimation for IRS-Aided Systems Exploiting 2...

引用

ieee 12th sensor array and multichannel signal processing workshop (SAM)

作者： Haider, Mirza Asif Chowdhury, Md. Waqeeb T. S. Zhang, Yimin D. Temple Univ Dept Elect & Comp Engn Philadelphia PA 19122 USA

ISBN: (纸本)9781665406338

Intelligent reflecting surface (IRS) is a promising next-generation technology for increasing channel capacity and reducing power consumption. In this paper, we present a novel IRS configuration consisting of a small number of active elements in an optimized L-shaped sparse array to separately estimate the channels between the base station and the IRS, and the channel between multiple user equipment and the IRS. Structured matrix completion techniques are used to attain superior direction-ofarrival estimation performance with an increased number of degrees of freedom. The training overhead is minimized in the proposed system and is not directly related to the number of IRS reflecting elements. The proposed sparse array strategy simultaneously resolves multiple sources with a high accuracy and outperforms the L-shaped uniform array counterpart using the same number of active elements. The effectiveness of the proposed strategy is confirmed using simulation results.

关键词： Intelligent reflecting surface active elements sparse array structured matrix completion channel estimation

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Channel Estimation and Indoor Positioning for Wideband Multiuser Millimeter Wave Systems 11

Channel Estimation and Indoor Positioning for Wideband Multi...

引用

ieee 11th sensor array and multichannel signal processing workshop (SAM)

作者： Lin, Yuxing Jin, Shi Matthaiou, Michail You, Xiaohu Southeast Univ Natl Mobile Commun Res Lab Nanjing Peoples R China Queens Univ Belfast Inst Elect Commun & Informat Technol ECIT Belfast Antrim North Ireland

ISBN: (纸本)9781728119465

We focus on channel estimation and indoor positioning of wideband multiuser millimeter wave systems. Leveraging the sparse channel characteristics, we transform the estimation problem to recovery problems of multipath parameters, e.g., angle of arrival, time delay and path fading. We model the training signal as a matricization form of a third-order canonical polyadic tensor, which consists of three factor matrices containing channel information. Inspired by array signal processing methods, we exploit the structural feature of our tensor and develop an uniqueness condition of tensor factorization, leading to a tensor-based channel estimation algorithm. In order to distinguish the multiuser signal components, we further develop a clustering-aided indoor positioning scheme. Simulation results show that the proposed methods apply to different system configurations and can achieve satisfactory estimation and positioning performance.

关键词： Channel estimation hybrid beamforming indoor positioning mmWave systems tensor signal processing

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Beamspace IQML

Beamspace IQML

引用

1st ieee sensor array and multichannel signal processing workshop (SAM 2000)

作者： Tian, Z Van Trees, HL George Mason Univ Ctr Excellence C3I Fairfax VA 22030 USA

ISBN: (纸本)0780363396

Iterative quadratic maximum likelihood (IQML) is an efficient approach for estimating the directions of arrival (DOA) of signals impinging on a uniform linear array. It is desirable to apply the IQML method in beamspace SO as to take advantage of the benefits of beamspace operations in terms of reduced computational complexity and improved resolution thresholds. The difficulty with beamspace IQML is that the Vandermonde structure of the array manifold may not preserve during the beamspace transformation. We tackle this obstacle using discrete Fourier transform (DFT) beams and derive a parameterized polynomial in the beamspace dimension. The proposed beamspace IQML algorithm is computationally efficient, and provides satisfactory estimation results.

关键词： IQML estimation beamspace processing polynomial parameterizations discrete Fourier transform matrices

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Receiver Antenna Allocation for Joint Sensing and Communications 13

Receiver Antenna Allocation for Joint Sensing and Communicat...

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13rd ieee sensor array and multichannel signal processing workshop (SAM)

作者： van der Werf, Ids Leus, Geert Chepuri, Sundeep Prabhakar Delft Univ Technol Delft Netherlands Indian Inst Sci Bengaluru India

ISBN: (纸本)9798350344820;9798350344813

We describe the problem of joint sensing and communications (JSAC) using an antenna array where some antennas are used for sensing and some others for communications. The problem is to jointly optimize the sensing and communications performance at the receive side through respectively the CramerRao bound (CRB) on the source angles and the variance of the sources after applying a minimum variance distortionless response (MVDR) beamformer. Both criteria are derived under a two-source scenario and optimized for any position of the two sources. Here one of the sources is considered the source of interest, while the other one models the interference. The performance criteria for sensing and communications are mathematically similar and depend only on the angular difference between the two sources. As a result, they can be elegantly combined and jointly optimized. Our findings are corroborated by simulations under different parameter settings.

关键词： Convex optimization Cramer-Rao bound sensor selection joint sensing and communication multi-target estimation

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A Blind Direction of Arrival and Mutual Coupling Estimation Scheme for Nested array 11

A Blind Direction of Arrival and Mutual Coupling Estimation ...

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ieee 11th sensor array and multichannel signal processing workshop (SAM)

作者： Shen, Jinqing Li, Jianfeng Zhu, Beizuo Ye, Changbo Nanjing Univ Aeronaut & Astronaut Coll Elect & Informat Engn Nanjing 211106 Peoples R China Nanjing Univ Aeronaut & Astronaut Key Lab Dynam Cognit Syst Electromagnet Spectrum Minisny Ind & Informat Technol Nanjing 211106 Peoples R China

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119465

Generally, nested array (NA) is susceptible to mutual coupling due to the dense subarray, which seriously degrades the performance. To address this issue, we design an array switching-based scheme to achieve the blind direction of arrival (DOA) and mutual coupling estimation in this paper. Specifically, by exploiting the inherent sparse structural characteristics of NA, we first switch the sparse subarray on to perform initial DOA estimation, which enables to offer the well-performed estimates free from the severe mutual coupling effect. Subsequently, the unambiguous angles are determined with low complexity by utilizing the received signal of the whole NA. Furthermore, the contaminated steering vector is reconstructed and a quadratic optimization problem is established to estimate the mutual coupling coefficients. Finally, re-estimation is conducted to obtain the refined estimates. Numerical simulations demonstrate the superiority of the proposed scheme.

关键词： nested array direction of arrival mutual coupling array switching

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Tracking Multiple Evolving Threats With Cluttered Surveillance Observations 10

Tracking Multiple Evolving Threats With Cluttered Surveillan...

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10th ieee sensor array and multichannel signal processing workshop (SAM)

作者： Sutton, Zachariah Willett, Peter Bar-Shalom, Yaakov Univ Connecticut Dept ECE Storrs CT 06269 USA

ISBN: (纸本)9781538647523

Many threats in the form of human actions (terrorist attacks, military actions, etc.) can be stochastically modeled by someone with relevant expert knowledge. In this work, a threat is taken to be a sequence of actions that evolve over time and culminate at some ultimate goal. A model would be a hypothesis as to how a threat would develop, and what kind of observable evidence it would produce along the way. This modeling method allows us to attempt detection using the preliminary evidence of a threat. This would theoretically allow the user to take preemptive action;i.e. the user can interfere with the threat before its culmination. This work presents a method of stochastically modeling these types of processes using Hidden Markov Models (HMMs). We then present a detection scheme based on random finite set (RFS) filters (Bernoulli filters) that allows for detection of multiple threat processes using a single cluttered stream of observed data.

关键词： Hidden Markov models Clutter Radio frequency Markov processes array signal processing sensor arrays"

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Real-time Kernel-based Multiple Target Tracking for Robotic Beating Heart Surgery

Real-time Kernel-based Multiple Target Tracking for Robotic ...

引用

8th ieee sensor array and multichannel signal processing workshop (SAM)

作者： Kurz, Gerhard Baum, Marcus Hanebeck, Uwe D. Karlsruhe Inst Technol KIT Intelligent Sensor Actuator Syst Lab ISAS Karlsruhe Germany Univ Connecticut Storrs CT USA

ISBN: (纸本)9781479914814

Performing surgery on the beating heart has significant advantages for the patient compared to traditional heart surgery on the stopped heart. A remote-controlled robot can be used to automatically cancel out the movement of the beating heart. This necessitates precise tracking of the heart surface. For this purpose, we track 24 identical artificial markers placed on the heart. This creates a data association problem, because it is not known which measurement was obtained from which marker. To solve this problem, we apply a multiple target tracking method based on a symmetric kernel transformation. This method allows efficient handling of the data association problem even for a reasonably large number of targets. We demonstrate how to implement this method efficiently. The proposed approach is evaluated on in-vivo data of a real beating heart surgery performed on a porcine beating heart.

关键词： symmetric measurement equation data association medical image processing

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Compressed Sensing Radar Surveillance Networks

Compressed Sensing Radar Surveillance Networks

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ieee 7th sensor array and multichannel signal processing workshop (SAM)

作者： Schmidt, Aurora Harley, Joel B. Moura, Jose M. F. Carnegie Mellon Univ Dept Elect & Comp Engn Pittsburgh PA 15213 USA

ISBN: (纸本)9781467310710

We study the problem of sensor fusion in a simplified radar surveillance application. A potentially large number of narrowband radars with isotropic antennas monitor a two-dimensional area for an unknown number of targets. We use techniques from compressive sensing to distribute efficient projections of network observations, allowing for reconstruction of the target scene using a single snapshot of sensor data. We avoid the use of a fusion node, allowing all radars to individually estimate target locations after iterative communication with neighboring sensors. We study the robustness of the discretization of continuous target locations, comparing estimation performance of basis pursuit reconstruction methods to a sparse estimator based on a model-robust formulation. We test the approach on simulated scenarios, showing tradeoffs in the resolution of target localization as well as the communication bandwidths required for this inter-radar cooperation scheme.

关键词： distributed radar sensor fusion consensus compressed sensing noise-aware basis pursuit model robust estimation

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Theoretical aspects of array radar imaging via fusing the experiment design and regularization techniques

Theoretical aspects of array radar imaging via fusing the ex...

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2nd ieee sensor array and multichannel signal processing workshop

作者： Shkvarko, YV Leyva-Montiel, JL IPN CINVESTAV Unidad Guadalajara Guadalajara 45090 Jalisco Mexico

ISBN: (纸本)0780375513

In this paper we address a new approach to solving the radar imaging problems stated and treated as ill-posed inverse problems of restoration of the spatial spectrum pattern of the wavefield sources distributed in the environment by processing the radar data signals distorted in the stochastic measurement channel. By exploiting the idea of combining the experiment design (ED) and descriptive regularization (R) theory methods for scattering inverse problems solution we propose a fused experiment-design-regularization (EDR) technique for radar image formation. With this technique we present the EDR-based interpretation of a family of the conventional array imaging algorithms and propose some their modifications to enhance the resolution performances of the resulting radar images.

关键词： Radar imaging

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