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Vertical-array-based Contour Reconstruction Algorithm for Airborne Weather Radar 11

Vertical-Array-based Contour Reconstruction Algorithm for Ai...

引用

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

作者： Wang, Yu Wu, Di Zhu, Daiyin Meng, Fanwang Nanjing Univ Aeronaut & Astronaut Key Lab Radar Imaging & Microwave Photon Nanjing 211106 Peoples R China Avic Leihua Elect Technol Res Inst Wuxi Jiangsu Peoples R China

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119465

Aiming at meteorological target, in this paper, a new contour reconstruction algorithm is proposed against the disastrous weather. The algorithm is capable of reconstructing the specific contour of meteorological target by exploiting vertical array of airborne weather radar system. First of all, Burg algorithm is utilized for the enhancement of beam spatial resolution in elevation dimension. Then, multi-beam algorithm is employed to form multiple beams and generate multiangle echoes, which further obtains more vertical contour information about weather scenario. Consequently the proposed algorithm, combining Burg algorithm and multi-beam algorithm, distinctly retrieves the vertical contour information and delivers a super-resolution behavior simultaneously. Using simulated radar data, the processing results demonstrate the validity of the presented algorithm. Compared with the so-called interpolation-based conventional methods, the proposed algorithm can achieve more comprehensive and accurate vertical contour reconstruction.

关键词： Vertical array airborne weather radar multi-beam vertical contour reconstruction

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Subspace-Based Localization of Near-Field signals in Unknown Nonuniform Noise 10

Subspace-Based Localization of Near-Field Signals in Unknown...

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

作者： Zuo, Weiliang Xin, Jingmin Zheng, Nanning Sano, Akira Xi An Jiao Tong Univ Inst Artificial Intelligence & Robot Xian 710049 Peoples R China Xi An Jiao Tong Univ Natl Engn Lab Visual Informat Proc & Applicat Xian 710049 Peoples R China Keio Univ Dept Syst Design Engn Yokohama Kanagawa 2238522 Japan

ISBN: (纸本)9781538647523

In this paper, we consider the problem of estimating the directions-of-arrival (DOAs) and ranges of multiple near-field narrowband signals impinging on a symmetric uniform linear array (ULA) in nonuniform noise in practical applications. By forming a Toeplitz-like correlation matrix from the anti-diagonal elements of the array covariance matrix to convert the nonuniform noise to a uniform one, a new subspace-based localization method is proposed, where the null space is obtained through eigendecomposition of the resultant Toeplitz-like matrix, and the MUSIC method is used to estimate the location parameters, while a new pairing scheme is presented as well. Additionally, an oblique projector based alternating iteration is presented to improve the estimation accuracy of the location parameters, where the "saturation behavior" encountered in most of localization methods is solved effectively. Furthermore, the Cramer-Rao lower bound (CRB) for the near-field signals in unknown nonuniform noise is also derived explicitly. Finally, the effectiveness of the proposed method is verified through numerical examples.

关键词： Near-field nonuniform noise oblique projector source localization statistical analysis uniform linear array

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SVM-based Tool to Detect Patients with Multiple Sclerosis Using a Commercial EMG sensor 10

SVM-based Tool to Detect Patients with Multiple Sclerosis Us...

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

作者： Akhmadeev, Konstantin Houssein, Aya Moussaoui, Said Hogestol, Einar A. Tutturen, Ingerid Harbo, Hanne F. Bos-Haugen, Steffan D. Graves, Jennifer Laplaud, David-Axel Gourraud, Pierre-Antoine Univ Nantes UMR 6004 LS2N Nantes France Ecole Cent Nantes UMR 6004 LS2N Nantes France Univ Oslo Inst Clin Med Dept Neurol Oslo Norway Oslo Univ Hosp Dept Neurol Oslo Norway Univ Calif San Francisco Sch Med Dept Neurol San Francisco CA USA Univ Nantes INSERM Ctr Rech Transplantat & Immunol UMR 1064 Nantes France

ISBN: (纸本)9781538647523

Multiple sclerosis (MS) is a major auto-immune disease that is the leading cause of non-traumatic impairment of the central nervous system (CNS) in young adults. Successful treatment of MS patients depends on accurate tools for both the MS diagnosis and the disability progression. In current and upcoming studies the authors aim to explore the capabilities of applying a commercial electromyographic and inertial sensor (MYO Armband by Thalmic Labs Inc.), coupled with a multichannel signal processing tool, to standard neurological examination of MS progression. In this pilot study we formulate a two-class "healthy control" - "having MS" classification problem. A dataset of electromyographic signals and inertial sensor measurements from 71 individuals (31 MS patients and 40 healthy controls) was acquired during standard neurological examination routine. Temporal and spectral features of the signals were extracted in order to train and validate a classification model. Finally, a Support Vector Machine classifier was obtained giving AUROC = 0.94, 95% CI = [0.88, 0.99]. We propose a set of signal descriptors that correlate with objective components of the neurological examination. The proposed signal acquisition and processing technique, being easy to integrate into the traditional neurological exam, may have high potential for aiding in quantifying MS progression.

关键词： Electromyography Feature extraction Protocols signal processing Support vector machines Multiple sclerosis Foot"

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STATISTICAL ANALYSES OF MEASURED FORWARD-LOOKING SONAR ECHO DATA IN A SHALLOWWATER ENVIRONMENT 12

STATISTICAL ANALYSES OF MEASURED FORWARD-LOOKING SONAR ECHO ...

引用

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

作者： Shen, Jiajun Gini, Fulvio Greco, Maria Sabrina Zhou, Tian Harbin Engn Univ Coll Underwater Acoust Engn Harbin 150001 Peoples R China Univ Pisa Dept Informat Engn I-56122 Pisa Italy Peng Cheng Lab Shenzhen 518055 Peoples R China

ISBN: (纸本)9781665406338

The performance of underwater target detection significantly depends on the statistical distribution of reverberation and knowledge of data correlation for active sonar. To reasonably design constant false alarm rate (CFAR) detectors that exploit knowledge of reverberation characteristics, a preliminary statistical analysis of active sonar echo data is necessary. In this study, we analyze the amplitude statistics of the measured forward-looking sonar echo data after applying the beamforming processing with a variety of distributions including log-normal, Weibull, Rayleigh, K, generalized Pareto (GP) and inverse Gaussian distributions. The results show that for the high-frequency sonar working in shallow water, both the K and the GP distributions can provide a good data fitting, while the GP distribution performs better especially in the tail region of the distribution. At last, the spatio-temporal correlation of data analysis and concluding remarks complete this paper.

关键词： Correlation array signal processing Statistical analysis Sonar measurements Sonar Sea measurements Tail

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Robust multi-sensor image registration using pixel migration

Robust multi-sensor image registration using pixel migration

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2nd ieee sensor array and multichannel signal processing workshop

作者： Keller, Y Averbuch, A Tel Aviv Univ Dept Elect Syst Engn IL-69978 Tel Aviv Israel

ISBN: (纸本)0780375513

This paper presents an energy minimization approach to registration of significantly dissimilar images, acquired by sensors of different modalities. The proposed algorithm introduces a robust matching criterion by aligning the locations of gradient maxima. The alignment is formulated as a parametric variational optimization problem which is solved iteratively by considering the intensities of a single image. The locations of the maxima of the second image's gradient are used as initialization. This implicit matching criterion is achieved while utilizing the full spatial information, without the need to use invariant image representations. We were able to robustly estimate affine and projective global motions using 'coarse to fine' processing, even when the images are characterized by complex space varying intensity transformations. These cause current state-of-the-art algorithms to fail. Finally, we present the registration of real images, which were taken by multi-sensor and multi-modality using affine and projective motion models.

关键词： Iterative methods

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An Improved Scheme for High-Resolution Point Cloud Map Generation Based on FMCW Radar 11

An Improved Scheme for High-Resolution Point Cloud Map Gener...

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

作者： Zheng, Qiangwen Xie, Yaping Yang, Lijie Li, Junjie Song, Chunyi Xu, Zhiwei Ding, Kai Zhejiang Univ Inst Marine Elect & Intelligent Syst Ocean Coll Hangzhou Peoples R China Key Lab Ocean Observat Imaging Testbed Zhejiang P Zhoushan Peoples R China Zhejiang Lab Hangzhou Peoples R China Zhejiang Inst Standardizat Hangzhou Peoples R China

ISBN: (纸本)9781728119465

For the frequency modulated continuous wave (FMCW) radar, the angle resolution of the generated point cloud map (PCM) is limited by both the number of receiver antennas and the interference of multi-target environments. This paper proposes an improved scheme for high-resolution PCM generation based on a 77 GHz FMCW radar system. The scheme consists of a method to synthesize an equivalent virtual array based on the time-division multiplexing (TDM) multiple-input multiple-output (MIMO) technique and an improved target detection algorithm based on multi-channel fusion. The results show that the proposed scheme could suppress the noise floor and improve the accuracy of target detection by 1.33 times compared to a conventional constant false alarm rate (CFAR) detector in a multi-target environment. Moreover, by applying the proposed scheme, the angle resolution of the PCM generated by the radar system reaches to 1.3022 degrees.

关键词： FMCW radar TDM-MIMO virtual array high-resolution point cloud map (PCM)

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Forward-looking planar array 3D-STAP using space time illumination patterns (STIP)

Forward-looking planar array 3D-STAP using space time illumi...

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4th ieee sensor array and multichannel signal processing workshop

作者： Corbell, Phillip M. Temple, Michael A. Hale, Todd B. SNHE Air Force Res Lab Hanscom AFB MA 01731 USA ENG Air Force Inst Technol Wright Patterson AFB OH USA

ISBN: (纸本)1424403081

Close-in sensing is needed for urban warfare operations, where Ground Moving Target Indication (GMTI) could be provided via forward or rear-facing multi-function array radars mounted on small highly-maneuverable airborne platforms. However, airborne radar arrays oriented any direction other than side-looking cause an elevation dependent angle-Doppler relationship in the clutter returns. This non-stationarity is acute in close-in sensing geometries where elevation diversity exists over the scene of interest. However, planar arrays have an inherent advantage over linear arrays due to their ability to observe clutter statistics as a function of elevation. This paper demonstrates the utility of elevation diversity by synthesizing a single 3D-STAP filter that exhibits an elevation dependent azimuth-Doppler response which is tailored to null the clutter "bowl" which characterizes the forward-looking clutter spectrum. Such a capability is particularly exploitable on transmit, where all elevation angles are simultaneously illuminated. To demonstrate potential benefits, this paper proposes the use of recently developed Space Time Illumination Patterns (STIP) from a planar AESA to invoke elevation diverse space-time illumination in a forward-looking clutter scenario. It is shown that 3D-STIP (azimuth-elevation-Doppler) facilitates elevation specific space-time beamforming which removes the clutter energy from a given Doppler frequency across all ranges, potentially simplifying processing on receive. Simulations using synthesized training data and clairvoyant covariance knowledge are conducted to demonstrate proof-of-concept.

关键词： Radar systems

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Reduced Dimensional 2-D DOA Estimation via Least Partial Search with Automatic Pairing for Parallel Co-prime arrays 11

Reduced Dimensional 2-D DOA Estimation via Least Partial Sea...

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

作者： Sun, Fenggang Ouyang, Shengqi Lan, Peng Li, Fengdi Shandong Agr Univ Coll Informat Sci & Engn Tai An Shandong Peoples R China North China Elect Power Univ Int Educ Inst Beijing Peoples R China

ISBN: (纸本)9781728119465

In this paper, we address the problem of two-dimensional (2-D) direction-of-arrival (DOA) estimation for parallel co-prime arrays. To alleviate the tremendous computation burden caused by spectral search and angle pairing, in this paper, we propose an efficient reduced dimensional least spectral search based estimation method with automatic pairing. Specifically, we first utilize the cross-covariance matrix to decouple the 2-D DOA estimation problem into a one-dimensional (1-D) one, and then design a least spectral search based 1-D DOA estimation method according to the relations between true and ambiguous angles. Finally, we estimate the remaining 1-D DOAs via least square criterion with automatic pairing. We evaluate the complexity and present the simulation results to show the effectiveness of the proposed method.

关键词： two-dimensional DOA estimation parallel co-prime array decoupled estimation least partial spectral search

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

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

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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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Distributed detection of correlated random processes under energy and bandwidth constraints

Distributed detection of correlated random processes under e...

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2014 ieee 8th sensor array and multichannel signal processing workshop, SAM 2014

作者： Maya, Juan Augusto Rey Vega, Leonardo Galarza, Cecilia G. Altieri, Andres University of Buenos Aires Buenos Aires Argentina CSC-CONICET Buenos Aires Argentina

ISBN: (纸本)9781479914814

We analyze a binary hypothesis testing problem built on a wireless sensor network (WSN). Using Large Deviation Theory (LDT), we compute the probability error exponents of a distributed scheme for detecting a correlated circularly-symmetric complex Gaussian process under the Neyman-Pearson framework. Using an analog scheme, the sensors transmit scaled versions of their measurements several times through a multiple access channel (MAC) to reach the fusion center (FC), whose task is to decide whether the process is present or not. In the analysis, we consider the energy constraint on each node transmission. We show that the proposed distributed scheme requires relatively few MAC channel uses to achieve the centralized error exponents when detecting correlated Gaussian processes. © 2014 ieee.

关键词： Wireless sensor networks

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