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Model for a smart network monitoring a wired sensor matrix

Model for a smart network monitoring a wired sensor matrix

引用

4th ieee sensor array and multichannel signal processing workshop

作者： Magagni, Luca Gennaretti, Davide Nicolini, Matteo Sergio, Maximilian Guerrieri, Roberto Canegallo, Roberto Univ Bologna ARCES I-40126 Bologna Italy STMicroelect FTM Agrate Brianza Italy

ISBN: (纸本)1424403081

Monitoring harsh environments such as underwater scenarios or aircraft external surfaces pertains to important applications like assisted navigation and tactical surveillance;nevertheless, it poses additional challenges compared with standard applications. At Transducers2005 we presented a wired addressing architecture of distributed sensors for monitoring real-time in-situ pressure variations in underwater environment that faces the above-mentioned issues. This architecture consists in a double array of identical and interconnected smart nodes monitoring a matrix of passive sensors. I n this paper, we present an analysis of the delay model related to the presented architecture and a calculation of the overall frame-rate of the system as a function of the geometrical topology of the arrays. The topology of the network, i.e. the length of each bus and the number of nodes, can be chosen according to the application, and directly affects the global capacitive load on the serial lines. Each serial line can be schematized with a distributed RC model for the flat cable plus a lumped capacitance for each smart node. Then, a 3(rd)-order pi-segmented model of O'Brien-Savarino [4] is calculated for a 16-block fine with block length equal to 0.3m. Thanks to that, the global time per iteration is calculated on each bus as well as the scanning time of the whole matrix and the frame rate for the system as a function of sensor distribution and of the aspect ratio of the matrix. This model can be employed to identify the optimal arrangement for the sensor matrix and smart node arrays.

关键词： Intelligent networks

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Expected Likelihood Approach for Covariance Matrix Estimation: Complex Angular Central Gaussian Case

Expected Likelihood Approach for Covariance Matrix Estimatio...

引用

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

作者： Abramovich, Yuri I. Johnson, Ben A. WR Syst 11351 Random Hills Rd Fairfax VA 22030 USA Lockheed Martin IS&GS Littleton CO 80137 USA UniSA Inst Telecommun Res Adelaide SA 5095 Australia

ISBN: (纸本)9781467310710

We consider the problem of covariance matrix estimation for strongly non-homogeneous data (clutter), modelled as spherically invariant complex random vectors. When normalized, such data are described by a complex angular Gaussian distribution. For a number of independent identically distributed (i.i.d.) samples with this distribution, we introduce the likelihood ratio and demonstrate that for the true covariance matrix, this LR has a p.d.f. which does not depend on the true matrix itself, but rather just its dimension and sample support. This "scenario-invariance" is used to select regularizing parameters that reduce the LR of the MLE estimate to a level statistically equal to the likelihood of the true covariance matrix. We apply this approach to select the loading factor in fixed point loaded covariance matrix estimates, and the order in the fixed point time-varying auto regressive (TVAR) covariance matrix estimate.

关键词： Expected Likelihood TVAR Estimation Order Estimation Diagonal Loading

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Distributed Posterior Cramer-Rao Lower Bound for Nonlinear Sequential Bayesian Estimation

Distributed Posterior Cramer-Rao Lower Bound for Nonlinear S...

引用

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

作者： Mohammadi, Arash Asif, Amir York Univ Toronto ON M3J 1P3 Canada

ISBN: (纸本)9781467310710

In distributed sensor networks, the posterior Cramer-Rao lower bound (PCRLB) has recently been used [1] as a selection criteria for sensor management decisions, where new sensor nodes are deployed or existing ones reactivated to optimize the network's performance. Previous algorithms to compute the PCRLB are derived for the centralized [2] and hierarchical architectures [3] using a fusion centre that makes them inappropriate for distributed sensor management. Only recently a suboptimal expression [1] for the distributed architecture has been proposed, which can at times lead to large errors especially in systems with highly non-linear dynamics. The paper derives the optimal PCRLB for the distributed architecture. In other words, we derive a recursive procedure to determine the overall Fisher information matrix (FIM), i.e., the inverse of the PCRLB, from local FIMs of the distributed estimators. The proposed distributed PCRLB is independent of the filtering mechanism used and closely follows its centralized counterpart.

关键词： Bayesian Estimation Distributed signal processing Particle Filters Posterior Cramer Rao Lower Bounds

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3D Parametric Channel Estimation for Multi-User Massive-MIMO OFDM Systems 11

3D Parametric Channel Estimation for Multi-User Massive-MIMO...

引用

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

作者： Liang, Junhui He, Jin Yu, Wenxian Shanghai Jiao Tong Univ Sch Elect Informat & Elect Engn Shanghai Peoples R China

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119465

In this paper, we study the problem of parametric channel estimation for multi-user 3D millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems. Modeling the channel by a finite number of multipath rays, we propose a new method to jointly estimate the elevation-azimuth angle and path delay parameters for a desired user. In the proposed method, a new version of subcarrier smoothing (SCS) is developed to construct a full rank correlation matrix. Then the 3D parameters are estimated by using the ESPRIT algorithm. Finally, simulation results are finally presented to verify the efficacy of the proposed algorithm.

关键词： ESPRIT multi-user 3D massive-MIMO OFDM channel estimation angle and delay estimation

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Multiple window bispectrum estimator

Multiple window bispectrum estimator

引用

4th ieee sensor array and multichannel signal processing workshop

作者： He, Huixia Thomson, David J. Queens Univ Kingston ON K7L 3N6 Canada

ISBN: (纸本)1424403081

By taking the third-order statistical information of processes into account, the bispectrum is a useful tool in digital signal processing and statistics. The paper proposes a nonparametric approach of estimating the bispectrum, using tapers designed to achieve maximal bifrequency concentration. Bispectra are functions of two frequencies plus their sum, so the optimum tapers are not products of Slepian sequences. The new tapers minintize the sixth-moment "energy" leakage in the estimate, and thus the new multiple window bispectrum estimator (MWBE) can be interpreted as minimizing the broad-band bias. Alternatively, the MWBE can be viewed as a solution of an integral inverse problem using an eigenfunction expansion. This approach can be extended to estimate higher-order polyspectra. Numerical simulations use moving average (MA) data with non-Gaussian white driving noise. Simulation results with small sample sizes show that this new MWBE is feasible and mean-squared error (MSE) optimal.

关键词： Digital signal processing

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Low-Overhead Cooperative Beamforming Under Imperfect Quantized SNR of Source-to-Relay Links

Low-Overhead Cooperative Beamforming Under Imperfect Quantiz...

引用

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

作者： Wu, Jwo-Yuh Hu, Chung-Hsuan Wang, Tsang-Yi Natl Chiao Tung Univ Dept Elect Engn 1001 Ta Hsueh Rd Hsinchu Taiwan Natl Sun Yat Sen Univ Inst Commun Engn Kaohsiung Taiwan

ISBN: (纸本)9781467310710

We consider a cooperative beamforming system with the amplify-and-forward protocol. To reduce the signaling overhead, each relay quantizes the SNR of the source-to-relay (S-R) link into one bit, which is then transmitted through a binary symmetric channel (BSC) with a known crossover probability to the destination. Given the set of the error-corrupted one-bit messages received at the destination, the beamforming design criterion is the maximization of the expected receive SNR, averaged over the conditional bit-flipping distributions of BSCs. We derive an analytic expression for the considered SNR metric, which is a complicated function of the beamforming weights. To facilitate analysis, we further derive a tractable lower bound for the conditional average SNR. By conducting maximization with respect to this lower bound, a closed-form sub-optimal beamformer can be obtained as a solution to a generalized eigenvalue problem. Computer simulations are used to illustrate the performance of the proposed scheme.

关键词： Cooperative communications amplify and forward relay beamforming overhead reduction quantization

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An efficient ISAR imaging method based on sliding window STAP 11

An efficient ISAR imaging method based on sliding window STA...

引用

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

作者： Li, Haodong Liao, Guisheng Xu, Jingwei Zhang, Jun Xidian Univ Natl Lab Radar Signal Proc Xian Peoples R China Xian Inst Elect Engn Business Div Air Borne Imaging Radar Xian Peoples R China

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119465

ISAR imaging for a marine moving target faces a series of challenges in the airborne radar system, especially the strong clutter interference with Doppler frequency spreading. To alleviate such problems, this paper proposes an efficient ISAR imaging method based on sliding window STAP. In the method, the whole CPI is divided into a series of coherent processing sub-intervals (CPSIs). Those CPSIs are generated with sliding window technique and they have identical length. In each CPSI, sub-CPI STAP is adopted to suppress the clutter. After that, the target signal is enhanced in terms of signal-to-clutter-plus-noise ratio (SCNR). Meanwhile, the Doppler frequency linear differences with respect to the azimuth dimension is still maintained, which contributes to the further ISAR imaging by Range-Doppler (rd) algorithm after range migration correction. Comparing with existing full-CPI STAP based method, the proposed method improves ISAR imaging performance while requiring less computational complexity. The simulation experiments are carried out to verify the effectiveness of the proposed method.

关键词： sliding window technique space-time adaptive processing long coherent processing interval strong clutter interference inverse synthetic aperture radar

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Semi-Passive RIS-Aided Sequential Channel Estimation and Prediction 13

Semi-Passive RIS-Aided Sequential Channel Estimation and Pre...

引用

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

作者： Haider, Mirza A. Zhang, Yimin D. Ding, Yanwu Shen, Dan Khanh Pham Chen, Genshe Temple Univ Dept Elect & Comp Engn Philadelphia PA 19122 USA Wichita State Univ Dept Elect & Comp Engn Wichita KS 67260 USA Intelligent Fus Technol Inc Germantown MD 20876 USA Air Force Res Lab Kirtland AFB NM 87117 USA

ISBN: (纸本)9798350344820;9798350344813

The popularity of mmWave in 5G and future communications is hindered by challenging propagation environments, such as line-of-sight obstruction. Reconfigurable intelligent surfaces (RIS) address this issue by dynamically modifying wireless channels, thereby enhancing data rates, reducing latency, and improving reliability in non-line-of-sight scenarios. For high data-rate communication and precise mobile user localization, a large RIS is required, resulting in a high pilot overhead for channel estimation. To address this issue, we exploit a semi-passive RIS with sparsely distributed active RIS elements in lieu of fully passive RIS. This approach efficiently enables channel estimation both between the base station and the RIS as well as between the RIS and the mobile users. Structured covariance matrix interpolation optimally utilizes the array aperture from the sparsely placed active RIS elements. Recognizing the need for frequent channel estimation, we introduce a recurrent neural network-based model for sequential channel prediction, resulting in a significant reduction of the required training pilot signals. Simulation results affirm the capability and effectiveness of the proposed approach to enhance data transmission.

关键词： Channel estimation reconfigurable intelligent surface sparse array neural network sequential learning

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Total Variation Compressive Sensing for Extended Targets in MIMO Radar 12

Total Variation Compressive Sensing for Extended Targets in ...

引用

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

作者： Roldan, Ignacio Fioranelli, Francesco Yarovoy, Alexander Delft Univ Technol Dept Microelect MS3 Delft Netherlands

ISBN: (纸本)9781665406338

The problem of extended target cross-section estimation has been considered. A two-step method based on the Total Variation Compressive Sensing theory has been proposed to solve it. First, a coarse estimation of the target cross-section is performed with classical beamforming methods, and then Compressive Sensing algorithms have been applied to refine it. To the best of the authors' knowledge, this is the first time this approach has been applied to automotive radar signals. The method has been verified simulating extended targets as scatter point clouds and computing the response in a uniform rectangular array. Two metrics have been used, the Intersection over Union and a pseudo Integrated Sidelobe Level. Significant improvements in both metrics compared with classical beamforming methods have been demonstrated.

关键词： Compressive Sensing Total Variation Normalization MIMO automotive radar Extended Targets

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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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