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14th IEEE International Conference on signal processing and Communications (SPCOM)

作者： Runwal, Bharat Vivek Kumar, Sandeep Indian Inst Technol Delhi New Delhi India Samsung Res Bangalore Bengaluru India

ISBN: (数字)9781665482509

ISBN: (纸本)9781665482509

Graph neural network (GNN) is achieving remarkable performances in a variety of application domains. However, GNN is vulnerable to noise and adversarial attacks in input data. Making GNN robust against noises and adversarial attacks is an important problem. The existing defense methods for GNNs are computationally demanding, are not scalable, and are architecture dependent. In this paper, we propose a generic framework for robustifying GNN known as Weighted Laplacian GNN (RWL-GNN). The method combines Weighted Graph Laplacian learning with the GNN implementation. The proposed method benefits from the positive semi-definiteness property of Laplacian matrix, feature smoothness, and latent features via formulating a unified optimization framework, which ensures the adversarial/noisy edges are discarded and connections in the graph are appropriately weighted. For demonstration, the experiments are conducted with Graph convolutional neural network(GCNN) architecture, however, the proposed framework is easily amenable to any existing GNN architecture. The simulation results with benchmark dataset establish the efficacy of the proposed method over the state-of-the-art methods, both in accuracy and computational efficiency.

关键词： Laplace equations Simulation Conferences signal processing algorithms Computer architecture signal processing Graph neural networks

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Automatic Dual-Polarized Ground Penetrating Radar for Enhanced 3-D Tree Roots System Architecture Reconstruction

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IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 2024年 62卷

作者： Luo, Wenhao Lee, Yee Hui Hao, Tong Yusof, Mohamed Lokman Mohd Yucel, Abdulkadir C. Tongji Univ Coll Surveying & Geoinformat Shanghai 200092 Peoples R China Tongji Univ Ctr Spatial Informat Sci & Sustainable Dev Applica Shanghai 200092 Peoples R China Nanyang Technol Univ Sch Elect & Elect Engn Singapore 639798 Singapore Natl Pk Board Singapore 259569 Singapore

Tree root systems are crucial for providing structural support and stability to trees. However, in urban environments, they can pose challenges due to potential conflicts with the foundations of roads and infrastructure, leading to significant damage. Therefore, there is a pressing need to investigate the subsurface tree root system architecture (RSA). Ground-penetrating radar (GPR) has emerged as a powerful tool for this purpose, offering high-resolution and nondestructive testing (NDT) capabilities. One of the primary challenges in enhancing GPR's ability to detect roots lies in accurately reconstructing the 3-D structure of complex RSAs. This challenge is exacerbated by subsurface heterogeneity and intricate interlacement of root branches, which can result in erroneous stacking of 2-D root points during 3-D reconstruction. This study introduces a novel approach using our developed wheel-based dual-polarized GPR system capable of capturing four polarimetric scattering parameters at each scan point through automated zigzag movements. A dedicated radar signal processing framework analyzes these dual-polarized signals to extract essential root parameters. These parameters are then used in an optimized slice relation clustering (OSRC) algorithm, specifically designed for improving the reconstruction of complex RSA. The efficacy of integrating root parameters derived from dual-polarized GPR signals into the OSRC algorithm is initially evaluated through simulations to assess its capability in RSA reconstruction. Subsequently, the GPR system and processing methodology are validated under real-world conditions using natural Angsana tree root systems. The findings demonstrate a promising methodology for enhancing the accurate reconstruction of intricate 3-D tree RSA structures.

关键词： Three-dimensional displays Image reconstruction Radar antennas Vegetation signal processing algorithms Accuracy Surveys Permittivity Ground penetrating radar Clustering algorithms 3-D reconstruction dual-polarized ground-penetrating radar (GPR) optimized slice relation clustering (OSRC) radar signal processing framework root system architecture (RSA)

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EXPECTATION CONSISTENT PLUG-AND-PLAY FOR MRI 47

EXPECTATION CONSISTENT PLUG-AND-PLAY FOR MRI

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47th IEEE International Conference on Acoustics, Speech and signal processing (ICASSP)

作者： Shastri, Saurav K. Ahmad, Rizwan Metzler, Christopher A. Schniter, Philip Ohio State Univ Dept ECE Columbus OH 43210 USA Ohio State Univ Dept BME Columbus OH 43210 USA Univ Maryland Dept CS College Pk MD 20742 USA

ISBN: (纸本)9781665405409

For image recovery problems, plug-and-play (PnP) methods have been developed that replace the proximal step in an optimization algorithm with a call to an application-specific denoiser, often implemented using a deep neural network. Although such methods have been successful, they can be improved. For example, the denoiser is often trained using white Gaussian noise, while PnP's denoiser input error is often far from white and Gaussian, with statistics that are difficult to predict from iteration to iteration. PnP methods based on approximate message passing (AMP) are an exception, but only when the forward operator behaves like a large random matrix. In this work, we design a PnP method using the expectation consistent (EC) approximation algorithm, a generalization of AMP, that offers predictable error statistics at each iteration, from which a deep-net denoiser can be effectively trained.

关键词： Magnetic resonance imaging Message passing Gaussian noise Neural networks signal processing algorithms signal processing Prediction algorithms

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RF-SITL: A Software-in-the-loop Channel Emulator for UAV Swarm Networks 23

RF-SITL: A Software-in-the-loop Channel Emulator for UAV Swa...

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23rd IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks (IEEE WoWMoM)

作者： Mastronarde, Nicholas Russell, Daniel Guan, Zhangyu Sklivanitis, George Pados, Dimitris Bentley, Elizabeth Serena Medley, Michael Univ Buffalo Dept Elect Engn Buffalo NY 14260 USA GE Aviat Grand Rapids MI 49512 USA Florida Atlantic Univ Dept Elect Engn & Comp Sci Boca Raton FL 33431 USA Air Force Res Lab AFRI I-13440 Rome NY Italy

ISBN: (数字)9781665408769

ISBN: (纸本)9781665408769

We introduce RF-SITL, a radio frequency (RF) software-in-the-loop (SITL) channel emulator developed with GNU Radio and the University at Buffalo's Airborne Networking and Communications (UB-ANC) emulator to enable integrated simulation of systems comprising multiple unmanned aerial vehicles (UAVs) interacting over a wireless communication channel. RF-SITL could be paired with any multi-robot simulator to enable I/Q sample-level fidelity simulation of communication interactions between the robots by accurately simulating channel effects, including interference, noise, distance-dependent path loss, and packet losses. RF-SITL works as follows: 1) it instantiates a virtual software-defined transceiver in GNU Radio for each UAV simulated in the UB-ANC Emulator;2) it builds an interference channel model in which each network node receives the superposition of signals transmitted from other nodes;and 3) it synchronizes the location of each simulated UAV in the UB-ANC Emulator with the virtualized RF transceivers in RF-SITL, such that the communication channel between nodes can accurately model distance-dependent channel effects, such as path loss. With these capabilities, we can use both off-the-shelf and custom-built signal processing flowgraphs that simulate Gaussian Minimum Shift Keying (GMSK), 802.11-like Orthogonal Frequency Division Multiplexing (OFDM), and direct sequence spread-spectrum (DSSS) links in GNU Radio to simulate swarm UAV networks prior to their deployment in software-defined radios in a swarm UAV network.

关键词： Radio frequency Wireless communication OFDM Atmospheric modeling signal processing algorithms Spread spectrum communication Autonomous aerial vehicles

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An improved event-by-event clustering algorithm for noisy acquisition 8

An improved event-by-event clustering algorithm for noisy ac...

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8th International Conference on Event-Based Control, Communication and signal processing (EBCCSP)

作者： Lesage, Xavier Tran, Rosalie Mancini, Stephane Fesquet, Laurent Univ Grenoble Alpes CNRS Grenoble INP TIMA F-38000 Grenoble France

ISBN: (纸本)9781665453493

Event-based image sensors are a new class of sensors developed thanks to non-uniform sampling and asynchronous technology, which overcomes many image sensor limitations such as a high throughput or a huge power consumption. As their behavior and outputs are really different from traditional image sensors, the produced data stream imposes to completely rethink image processing. Indeed, dedicated algorithms are mandatory to take advantage of this specific data stream, known as Address Event Representation (AER). This paper presents an improved and dedicated event-by-event clustering algorithm allowing the object detection in a noisy environment which is still performant with a SNR of 1/4. We measure high recall and precision for different simulated scenarios with multiple objects and show an improvement compared to the previous algorithm. The approach especially demonstrates a low computational complexity and a reduced memory footprint, which is perfectly suited for low-cost and low-power embedded image sensing applications.

关键词： Image sensors signal processing algorithms Clustering algorithms Streaming media signal processing Throughput Robustness

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A New Outage Probability Bound for IR-HARQ and Its Application to Power Adaptation 23

A New Outage Probability Bound for IR-HARQ and Its Applicati...

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23rd International Workshop on signal processing Advances in Wireless Communication (SPAWC)

作者： Wang, Wenyu Shen, Kaiming Chinese Univ Hong Kong Sch Sci & Engn Shenzhen Peoples R China

ISBN: (数字)9781665494557

ISBN: (纸本)9781665494557

This work proposes a novel upper bound on outage probability for the incremental redundancy hybrid automatic repeat request (IR-HARQ) protocol over block fading channels. The new bound is much tighter than the classical bound due to Laneman, especially when the transmit power is limited as is often the case in the Internet of Things (IoT). We demonstrate the practical use of this new bound by showing that it enables a geometric programming approach to power adaptation for IR-HARQ. Because the new bound approximates the outage probability much more exactly, the resulting new power adaptation scheme significantly outperforms those existing methods based on the classical bound.

关键词： Fading channels Wireless communication Upper bound Protocols Redundancy signal processing algorithms Probability

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PolyDot Coded Privacy Preserving Multi-Party Computation at the Edge 23

PolyDot Coded Privacy Preserving Multi-Party Computation at ...

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23rd International Workshop on signal processing Advances in Wireless Communication (SPAWC)

作者： Vedadi, Elahe Keshtkarjahromi, Yasaman Seferoglu, Hulya Univ Illinois Chicago IL 60680 USA Seagate Technol Cupertino CA USA

ISBN: (数字)9781665494557

ISBN: (纸本)9781665494557

We investigate the problem of privacy preserving distributed matrix multiplication in edge networks using multi-party computation (MPC). Coded multi-party computation (CMPC) is an emerging approach to reduce the required number of workers in MPC by employing coded computation. Existing CMPC approaches usually combine coded computation algorithms designed for efficient matrix multiplication with MPC. We show that this approach is not efficient. We design a novel CMPC algorithm;PolyDot coded MPC (PolyDot-CMPC) by using PolyDot codes. We exploit "garbage terms" that naturally arise when polynomials are constructed in the design of PolyDotCMPC to reduce the number of workers needed for privacypreserving computation. We show that entangled polynomial codes, which are consistently better than PolyDot codes in coded computation setup, are not necessarily better than PolyDotCMPC in MPC setting.

关键词： Wireless communication Privacy Codes Conferences signal processing algorithms signal processing Multi-party computation

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Terahertz ISAR Imaging With Nonrigid Vibration Compensation and Sidelobe Suppression of Space Targets

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IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 2024年 62卷 1页

作者： Yuan, Zhian Chen, Xu Deng, Bin Yi, Jun Tang, Bin Wan, Jianwei Wang, Hongqiang Wang, Ruijun Natl Univ Def Technol NUDT Coll Elect Sci & Technol Changsha 410073 Peoples R China Harbin Engn Univ HEU Coll Informat & Commun Engn Harbin 150006 Peoples R China Air Force Engn Univ Air Def & Antimissile Sch Xian 710043 Peoples R China

Terahertz (THz) inverse synthetic aperture radar (ISAR) imaging of space targets has the advantage of high resolution and all-day capability for spatial situational awareness (SSA). However, compared with microwave ISAR imaging, microvibrations of the radar platform and target can cause image defocusing and quality degradation in the THz band. Commonly, the existing algorithms considered vibration as simple harmonic motion in a rigid body and estimated the vibration parameters for phase error compensation. Nevertheless, these methods are dependent on the prominent points and cannot focus on the complex nonrigid vibration of the space target. Aiming at these problems, an ISAR imaging framework that can be leveraged for complex nonrigid vibration compensation is proposed. First, a compressed sensing (CS) model is established to compensate for the vibration phase error in ISAR imaging. Then, the alternating direction method of multipliers (ADMMs) is employed to optimize the CS model. Subsequently, considering that strong scattering points of space targets will cover up the weak scattering information in ISAR images, a sidelobe suppression constraint is appended. Thus, the weak scattering information is retained while removing the sidelobe and noise. It is worth mentioning that the ISAR imaging algorithm is derived to a 2-D matrix form to reduce memory usage and improve computational efficiency. Finally, simulated and measured data are utilized to verify the superiority of the proposed algorithm and prove the potential of ISAR imaging for practical space targets.

关键词： Vibrations Imaging Radar imaging Scattering Radar Space vehicles signal processing algorithms Alternating direction method of multipliers (ADMMs) inverse synthetic aperture radar (ISAR) sidelobe suppression terahertz (THz) radar vibration compensation

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FL-PFA: A Polar Format Algorithm for Wide-Beam Forward-Looking SAR Imaging Integrating Spatial-Variant Motion Compensation

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IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 2024年 62卷 1-1页

作者： Meng, Zhichao Zhang, Lei Lu, Jingyue Wang, Xinshuo Sun Yat Sen Univ Sch Elect & Commun Engn Shenzhen 518107 Peoples R China Xidian Univ Sch Comp Sci & Technol Xian 710071 Peoples R China Xidian Univ Natl Key Lab Radar Signal Proc Xian 710071 Peoples R China

Multichannel forward-looking synthetic aperture radar (FLSAR) imaging presents challenges due to spatiotemporal coupling, especially in wide-beam scenarios. This article introduces a new polar format algorithm (PFA) called the forward-looking polar format algorithm (FL-PFA) for wide-beam FLSAR imaging. The proposed algorithm utilizes a time-space-time hybrid scheme to address the spatiotemporal coupling, matching the spatiotemporal structure of FLSAR echoes. Furthermore, the scheme combines spatial-variant motion compensation (MOCO) and polar format imaging, resulting in an efficient processing flow. For spatial-variant MOCO, this article introduces an adaptive subaperture topography- and aperture-dependent (ASATA) algorithm, offering the advantage of balancing compensation accuracy and efficiency using adaptive optimal subapertures. Subsequently, a novel PFA is proposed to obtain a focused FLSAR image. In the PFA, the azimuth angle wavenumber considers both the spatial-variant quadratic phase and residual motion errors, aligning with the spatial-variant Doppler modulation rate characteristic of FLSAR. By resampling the azimuth angle wavenumber, a well-focused FLSAR image on the polar coordinate grid and more accurate MOCO can be achieved simultaneously. Finally, extensive experiments using simulated and actual synthetic aperture radar (SAR) data demonstrate the superiority of FL-PFA.

关键词： Imaging Azimuth Doppler effect Synthetic aperture radar signal processing algorithms Image resolution Spatiotemporal phenomena Adaptive subaperture topography- and aperture-dependent (ASATA) forward-looking synthetic aperture radar (FLSAR) polar format algorithm (PFA) spatial-variant motion compensation (MOCO)

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Sample Pose Augmentation and Adaptive Weight-Based Refinement for 3-D LiDAR-Camera Extrinsic Calibration Using an Orthogonal Trihedron

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IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 2024年 73卷 1页

作者： Choi, Yeongyu Park, Ju H. Jung, Ho-Youl Yeungnam Univ Dept Informat & Commun Engn Gyongsan 38541 South Korea Yeungnam Univ Dept Elect Engn Gyongsan 38541 South Korea

Light detection and ranging (LiDAR) and cameras are core sensors used in autonomous vehicles and industrial robots. LiDAR-camera fusion systems require an accurate estimation of the relative pose to integrate different sensor data. We propose an offline method for 3-D LiDAR-camera extrinsic calibration using an orthogonal trihedron with checkered patterns on each plane. Our approach for LiDAR pose estimation consists of four steps: background rejection, perpendicularity enforcement, dominant pose decision, and refinement. In the iterations of the first and second steps, several poses are sampled. The sample poses are evaluated and augmented, then the highest scoring sample is determined as the dominant pose. For the refinement, a new loss function with adaptive weights is introduced, which is formulated as the minimization of the sum of the squared distance between points and the nearest plane on the target. The relative pose is estimated by solving the perspective-n-point (PnP) problem. Our experimental results through simulations in various noise scenarios show that the proposed method estimates the relative poses with higher accuracy and stability compared to existing methods, in terms of the mean and standard deviation of errors. The source code is available at https://***/ygchoi11/3DLiDAR-Camera_Calibration.

关键词： Extrinsic calibration M-estimator sample consensus (MSAC) random sample consensus (RANSAC) sensor fusion signal processing algorithms

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