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14th IEEE image, Video, and Multidimensional signal processing Workshop (IVMSP)

作者： Juven, Alexis Aumeunier, Marie-Helene Brunet, Romain Le Bohec, Mickael Adel, Mouloud Miorelli, Roberto Artusi, Xavier Reboud, Christophe CEA IRFM St Paul Les Durance Cadarache France Aix Marseille Univ Inst Fresnel UMR 7249 Cent MarseilleCNRS F-13013 Marseille France Univ Paris Saclay CEA List F-91120 Palaiseau France

ISBN: (纸本)9781665478229

Infrared (IR) imaging systems are common diagnostics for monitoring in-vessel components in thermonuclear fusion devices (tokamak). Nevertheless, IR interpretation in fully metallic environment is complex due to the presence of multiple reflections and the change of optical properties of materials as the fusion operation progresses. This causes high errors on the surface temperature measurement which is a risk for machine protection. The paper presents a first demonstration of simulation-assisted machine learning method for retrieving the surface temperature from IR measurement on metallic targets with unknown properties. The technique relies on the training of a convolutional neural network on a synthetic dataset generated by a deterministic ray tracer. The performances of such an approach is first proven on tokamak prototype considering pure specular surfaces.

关键词： Temperature measurement Training performance evaluation Temperature distribution Prototypes Machine learning Tokamak devices

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5th International Workshop on New Approaches for Multidimensional signal processing, NAMSP 2024

5th International Workshop on New Approaches for Multidimens...

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5th International Workshop on New Approaches for Multidimensional signal processing, NAMSP 2024

ISBN: (纸本)9789819624812

The proceedings contain 28 papers. The special focus in this conference is on New Approaches for Multidimensional signal processing. The topics include: Jamming image Recognition Problem;performance evaluation of Surface Defect Segmentation with an Novel Battery Surface RGB Dataset;dynamic Tensor Least Angle Regression Using L1 Homotopy;multidimensional signal Analysis of Colorectal Cancer Using Bioinformatic Techniques;performance evaluation of Workpiece Counting Neural Network with a Novel Sketch Dataset for Reducing Background Noise;entity Resolution Using Transformers for Synthetic Datasets;sound-Driven Identification of South African Birds;application of Deep Learning Models for Multimodal Information Fusion in Intelligent Information Classification;an Introductory Glimpse of Machine Learning Applications in Multidimensional signal Analysis;electromyography-Based Hand Movement Detection Using Machine Learning Algorithm;research on the Application of Reinforcement Learning in Film Script Generation and Narrative Innovation;design of Publicity Animation Sample Based on Dynamic simulation Technology;research on image Enhancement Technology Based on Semi-Supervised Learning for Oil Painting image;performance Analysis of Digital Control Oscillator Using Ant Colony Optimization;a Study on the Application of Different Types of Electric Motors as Electric Vehicles’ Drives and on the Necessity of 3D image Analysis;a Deep Learning-Based Study of Adolescents’ Self-Esteem Developmental Patterns: Exploring the Intersection of Psychology and Data Science;research on Interactive Experience of Virtual Reality Technology in Oral English Teaching;A SOM Algorithm for Chronic Hepatitis B Drug Expenditure Forecast;construction of Knowledge Map and Design of Decision Support System for Diagnosis of Tumor Disease;intelligent Hotel Management System Combined with Facial Recognition Technology.

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Imaging infrared seeker design and tests for FOK guided missile 34

Imaging infrared seeker design and tests for FOK guided miss...

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Conference on Infrared Imaging systems - Design, Analysis, modeling, and Testing XXXIV

作者： Leshchenko, Yelyzaveta Kaczmarek, Kacper Labaj, Filip Malecki, Szymon Miedzinski, Dariusz Sochacki, Mateusz Warsaw Univ Technol Inst Micromech & Photon Fac Mechatron Student Club Photon Engn SPIE & Opt Chapter Andrzeja Boboli 8 PL-02525 Warsaw Poland Warsaw Univ Technol Fac Power & Aeronaut Engn Students Space Assoc Nowowiejska 21-25 PL-00665 Warsaw Poland Warsaw Univ Technol Inst Microelect & Optoelect Doctoral Sch Koszykowa 75 PL-00662 Warsaw Poland Polish Armaments Grp SA Nowy Swiat 4 PL-00497 Warsaw Poland Warsaw Univ Technol Fac Power & Aeronaut Engn Inst Aeronaut & Appl Mech Div Mech Nowowiejska 24 PL-00665 Warsaw Poland Warsaw Univ Technol Fac Power & Aeronaut Engn Inst Aeronaut & Appl Mech Div Automat & Aeronaut Syst Nowowiejska 24 PL-00665 Warsaw Poland

ISBN: (纸本)9781510661806;9781510661813

The design, development and performance evaluation of an imaging infrared seeker system of the FOK missile will be presented in this paper. FOK is a guided missile iteratively developed since 2017 by the Students' Space Association at Warsaw University of Technology, designed as a testbed for the development of control algorithms. Throughout the years of development the design evolved, and currently assumes the incorporation of an electro-optical seeker, enabling the missile to actively search and track ground-based targets. An infrared detection module was chosen as the core sensing component of the system. The module consists of an uncooled 640x512 microbolometer detector array integrated with dedicated optics, providing a high-resolution image in the 8-12 mu m spectral range. Since the seeker will be mounted at the front of the missile, an IR-transparent nose cone dome was required as part of the optical system. Two dome variants were designed, made out of silicon and germanium, respectively. Optical parameters of the imaging system, composed of the dome - objective - microbolometer array were calculated and confirmed using ray-tracing software. The designed domes were optimized in order to minimize image quality degradation. Key parameters considered during the calculations included: optical aberrations, modulation transfer function - MTF and field of view - FOV. Software-in-the-loop tests with the use of in-house developed simulation software will be performed together with hardware-in-the-loop tests based on capturing real images obtained by the tested system installed under a UAV. The tests' goal was to check the performance of the developed guidance algorithms in an operational-like environment.

关键词： electro-optical seeker missile guidance guidance algorithm thermal imaging long-wave infrared infrared optics microbolometers focal plane array image processing

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A Model-Based Approach Digital Pre-Distortion Method for Current-Steering Digital-to-Analog Converters

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IEEE TRANSACTIONS ON CIRCUITS AND systems I-REGULAR PAPERS 2022年第11期69卷 4583-4595页

作者： Valet, Patrick Schwingshackl, David Gaier, Ulrich Tonello, Andrea M. MaxLinear Austria GmbH A-9524 Villach Austria Alpen Adria Univ Klagenfurt Inst Embedded Syst A-9020 Klagenfurt Austria

This paper presents a novel static digital pre-distortion (DPD) method for a current-steering digital-to-analog converter (CS-DAC). The proposed method utilizes the knowledge of the current cell array architecture to calculate the static mismatch currents of the cells. The mismatch values are stored in memory and added to the original input code to generate the new pre-distorted input word. The converter corrects the static error with its own current cells without incorporating an additional calibration DAC (CALDAC) or programmable current sources. This results in a reduction in area, power and simulation run times because of the simpler circuit design. An Overflow-Cell-Selection (OCS) is introduced as a novel solution to further enhance the static linearity of the converter. It also can be implemented as a software solution for already existing DAC designs which do not have an integrated DPD and lab/measurement equipment (e.g., arbitrary wave generator (AWG)). This poses as a strong differentiation factor compared to other state-of-the-art static DPD methods. The evaluation of the proposed DPD is done via simulations in MATLAB and on-chip measurements with a 14-bit CS-DAC in 16 nm. Single tone measurements show a performance gain of the total harmonic distortion (THD) of 12 dB.

关键词： Computer architecture Microprocessors Calibration Switches Mathematical models Integrated circuit modeling Codes Digital pre-distortion calibration DAC current-steering digital-analog conversion MATLAB signal processing

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A Methodology for Verifying and Validating the Functional performance evaluation of High-Fidelity RADAR Sensor Models at Raw Data and Detection Levels

A Methodology for Verifying and Validating the Functional Pe...

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International Conference on Vision, image and signal processing (ICVISP)

作者： Arsalan Haider Lukas Haas Abduelkadir Eryildirim Thomas Zeh Shotaro Koyama Nils Henning Müllner Martin Jakobi Alexander W. Koch IFM-Institute for Driving Assistance and Connected Mobility Kempten University of Applied Sciences Germany Institute for Measurement Systems and Sensor Technology Technical University of Munich Germany Infineon Technologies Austria AG Advanced Vehicle Research Institute Kanagawa Institute of Technology Japan Institute of Transportation Systems German Aerospace Center DLR Germany

ISBN: (数字)9798331541460

ISBN: (纸本)9798331541477

This paper outlines a comprehensive methodology for verifying and validating the functional performance evaluation of high-fidelity radio detection and ranging (RADAR) sensor models at both the raw data level, specifically the range map (RM) and range-Doppler map (RDM), and the detection level. Three key performance parameters (KPPs) are defined at the raw data level: the target's received power, signal-to-noise ratio (SNR), and twoway beam pattern. Four KPPs are identified at the detection level: distance, relative radial velocity, azimuth angle, and elevation angle. This study also introduces three dynamic test scenarios directly applicable to the functional evaluation assessment of RADAR sensor models. Furthermore, a toolchain is presented to integrate real-world test scenarios into the virtual environment, allowing for frame-by-frame validation of the RADAR sensor models' functional evaluation. Quantitative analysis successfully assesses differences between simulations and real measurements, employing the mean absolute percentage error (MAPE) metric. This methodology has been successfully applied to a high-fidelity RADAR sensor model featuring a multiple input and multiple output (MIMO) 2D linear spacing virtual antenna and a complete signal processing toolchain that mimics real RADAR sensors. Results show a strong correlation between the simulation and real measurements, with MAPE values below 7 % for all defined KPPs at raw data and detection levels. Using this methodology, developers can assess whether virtual RADAR sensors are ready for environmental perception during scenario-based automated driving system (ADS) testing.

关键词： performance evaluation Correlation Radar detection Radar Radar antennas Data models Radar signal processing Distance measurement signal to noise ratio Testing

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AntoNet: A Small Linear Contrast-Enhancing CNN for Pixel-Wise Detection

AntoNet: A Small Linear Contrast-Enhancing CNN for Pixel-Wis...

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Workshops on image processing Theory, Tools and Applications, IPTA

作者： Soggia Antonio Fillatre Lionel Deruaz-Pepin Laurent Thales DMS I3S Sophia-Antipolis France CNRS I3S Université Côte d'Azur Sophia-Antipolis France Thales DMS Sophia-Antipolis France

ISBN: (数字)9798331541842

ISBN: (纸本)9798331541859

In current broadband passive sonar systems, a human operator observes a 2D image that represents different energy levels in the bearing and time dimensions. The temporal depth of the image helps the operator to detect and identify the paths taken by different sources. However, detecting weak noise sources amid ambient sea noise and strong sources can be challenging. The purpose of this work is to increase the contrast of those images using AI techniques. The performance of AntoNet, our proposed architecture based on Unet, is evaluated for reducing ambient noise and enhancing the signal of interest. The dataset is generated by a fast sonar image simulator based on a simplified sonar beamforming model. We aim to improve pixel-wise detection through clearer 2D images with a better SNR. AntoNet leverages the temporal depth of data to produce 2D images with an enhanced SNR while having less than 1,500 parameters. performance evaluation demonstrates AntoNet's effectiveness in single source environments, achieving higher detection performance with minimal artifacts.

关键词： Training performance evaluation Computational modeling Sonar applications Memory management Decision making Feature extraction Real-time systems Energy states signal to noise ratio

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Analog Implementation of Weighted Median Filter

Analog Implementation of Weighted Median Filter

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Smart systems for Electrical, Electronics, Communication and Computer Engineering (ICSSEECC), International Conference on

作者： Kaliamoorthy M Vasna lija SJ Nithish Kumar D Mukeshkumar B Department of EEE Dr. Mahalingam College of Engineering and Technology Tamilnadu India

ISBN: (数字)9798350378177

ISBN: (纸本)9798350378184

This paper presents an analog implementation of a Weighted Median Filter (WMF) using 90nm CMOS (Complementary Metal-Oxide-Semiconductor) technology. WMF is an effective tool for image denoising because it can preserve edges while effectively reducing noise. The proposed analog implementation takes advantage of CMOS technology's low power consumption and compact size to realize a hardwareefficient solution appropriate for real-time applications. The design begins with a detailed analysis of the weighted median filtering algorithm, with a focus on the computation of the weighted median and its implementation challenges in the analog domain. Additionally, submicron CMOS technologies' inherent process fluctuations and device mismatch are minimized through the optimization of the analog circuitry. Sizing optimization and biasing are two strategies used to guarantee reliable performance around corners of the process. The suggested analog weighted median filter effectively suppresses noise while maintaining image features, as shown by the simulation results. The concept can be integrated into highperformance, low-power imaging systems since it achieves competitive performance metrics in terms of mean square error (MSE), processing speed, and signal-to-noise ratio (SNR). All things considered, this study advances the use of analog signal processing methods in contemporary semiconductor technology and provides a workable answer for noise reduction in image sensor applications in real time.

关键词： performance evaluation image sensors Power demand simulation Noise reduction Mean square error methods CMOS technology

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Digital Filter Architecture With Calculations in the Residue Number System by Winograd Method F (2 x 2, 2 x 2)

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IEEE ACCESS 2021年 9卷 143331-143340页

作者： Valueva, Maria Lyakhov, Pavel Valuev, Georgii Nagornov, Nikolay North Caucasus Fed Univ North Caucasus Ctr Math Res Stavropol Russia North Caucasus Fed Univ Dept Math Modeling Stavropol 355017 Russia St Petersburg Eleetrotech Univ LETI Dept Automat & Control Proc St Petersburg 197376 Russia

Improving the technical characteristics of digital signal processing devices is an important problem in many practical tasks. The paper proposes the architecture of a device for two-dimensional filtering in a residue number system (RNS) with moduli of a special type according to the Winograd method. The work carried out the technical parameters theoretical analysis of the proposed filter architecture for different RNS moduli sets by the "unit-gate"-model. In addition, the proposed architecture is compared with known digital filter implementations. The theoretical analysis results showed that the use of the proposed filter architecture makes it possible to increase the signal processing speed by 1.33 - 6.90 times, in comparison with the known device implementations. Also, in the work, the hardware simulation of the proposed filter architecture was performed on FPGA, which showed that the performance of the proposed device is 1.31 - 4.12 times higher than known digital filter architectures. The research results can be used in digital signal processing systems to increase their performance and reduce hardware costs. In addition, the developed architectures can be applied in the development of hardware accelerators for complex digital signals analysis systems.

关键词： Filtering Digital filters performance evaluation Computer architecture Hardware Field programmable gate arrays Filtering algorithms Digital filters residue number system Winograd method

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8th International Conference on signal and Information processing, Network and Computers, ICSINC 2021

8th International Conference on Signal and Information Proce...

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8th International Conference on signal and Information processing, Network and Computers, ICSINC 2021

ISBN: (纸本)9789811933868

The proceedings contain 178 papers. The special focus in this conference is on signal and Information processing, Network and Computers. The topics include: Research on Real-Time Monitoring Method of Spot Beam Antenna Direction on Satellites;A Novel SOC Estimation Approach for the Lithium-Ion Battery Pack Using in the Deep Space Landers;Analysis of Characteristics and Requirements of Large LEO Constellations Management;research on Space Project systems Technological Risk Assessment Based on Multi-level Fuzzy Comprehensive evaluation;research on the System Construction of Spaceborne Adaptive Software and Its Key Technologies;air-Space-Ground Integrated Information Network: Technology, Development and Prospect;high-Resolution Satellite Radiation Big Data All-Statistical Intelligent Screening Technology;EMC System Control on XX-2 Satellite;transmission and Control of the image Data from Remote Sensing Satellite to the Ground Station;micro-vibration Attenuation Design, Analysis and Verification for Agile Remote Sensing Satellite;LDPC Coding and Decoding Algorithm of Satellite Communication in High Dynamic Environment;Practice and Research on FMEA of Telecommunication Satellite System;characterization of On-Orbit Temperature and Pressure performance for Hydrazine Propulsion System;On-Orbit Calibration of a 7-DOF Space Arm;correlation Analysis and Forecast of Electric Vehicle Charging Stations Considering Seasonal Factors;Inversion modeling Study of Dissolved Oxygen in Wangyu River Based on BP Neural Network;research on Satellite Energy Autonomous Security Strategy;Research and Development of High Speed and Large Bandwidth MIMO Data Transmission Test System;Continuous Evolution for Efficient Neural Architecture Search Based on Improved NSGA-III Algorithm;research on Individual Identification of Radar Emitter Based on Multi-domain Features.

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Residual Error Feedback Zeroing Neural Network for Solving Time-Varying Sylvester Equation

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IEEE ACCESS 2022年 10卷 2860-2868页

作者： Li, Kunjian Jiang, Chengze Xiao, Xiuchun Huang, Haoen Li, Yongjiang Yan, Jingwen Guangdong Ocean Univ Sch Elect & Informat Engn Zhanjiang 524088 Peoples R China Guangdong Ocean Univ Sch Math & Comp Zhanjiang 524088 Peoples R China Shantou Univ Coll Engn Shantou 515063 Peoples R China

In many fields, the issue of solving the time-varying Sylvester equation (TVSE) is commonly encountered. Consequently, finding its exact solution has become a research hotspot. In general, the ZNN and IEZNN models are the most useful algorithms that are frequently utilized to solve the TVSE problem. However, the ZNN model is borned with noise susceptibility and the IEZNN model loses the adaptive performance due to its constant coefficient in solving the TVSE problem. In this paper, a residual error feedback zeroing neural network (REFZNN) is proposed to adaptively solve the TVSE problem. The REFZNN model feeds back the residual error to the solustion system, which forms a feedback regulation to reduce the residual error between the system output and the system target. Then, the convergence and noise patience of the REFZNN model are proved by theoretical analyses. Finally, the validity of the proposed model is verified by designing computer simulation experiments and its superiority is confirmed by the performance comparisons with the ZNN and IEZNN models.

关键词： Mathematical models Computational modeling Adaptation models Convergence Analytical models Education Adaptive systems Time-varying problems residual error feedback zeroing neural network (ZNN) Sylvester equation

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