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Overdemodulation-Aided One-Bit DoA Estimation

Overdemodulation-Aided One-Bit DoA Estimation

引用

sensor array and multichannel signal processing workshop

作者： Saeid Sedighi Bhavani Shankar Mysore R Björn Ottersten Valeo Schalter und Sensoren GmbH Interdisciplinary Centre for Security Reliability and Trust (SnT) University of Luxembourg

ISBN: (数字)9798350344813

ISBN: (纸本)9798350344820

Sensing and communication systems commonly employ quadrature demodulation for signal down-conversion to baseband, using two orthogonal sinusoidal signals–an approach well-suited for systems equipped with high-resolution Analog-to-Digital Converters (ADCs). However, the performance of this approach is compromised when constrained to one-bit resolution ADCs. Motivated by this fact, in this paper, we explore the problem of one-bit DoA estimation, where the received signal is deliberately overdemodulated using multiple offset sinusoidal signals in the coherent analog down conversion before being processed by a one-bit ADC. Through numerical analysis, we reveal that the overdemodulation technique substantially enhances the accuracy of one-bit DoA estimation.

关键词： Direction-of-arrival estimation Accuracy array signal processing Numerical analysis Conferences Estimation sensors

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Compressive noise radar for urban sensing

Compressive noise radar for urban sensing

引用

sensor array and multichannel signal processing workshop

作者： Mahesh C. Shastry Ram M. Narayanan Muralidhar Rangaswamy Corporate Research Lab 3M Company Saint Paul MN Electrical Engineering Department Pennsylvania State University PA Air Force Research Lab Purdue University West Lafayette IN

Ultra-wideband (UWB) noise-like transmit waveforms are ideally suited for implementing compressive radar range-profile imaging systems. Due to useful properties such as robustness to interference, simplicity of hardware design, and high range resolution, UWB noise radar has been successfully applied to urban-sensing scenarios. Compressive noise radar systems can achieve resolutions comparable to conventional systems at lower sampling rates, thus enabling super-resolution in radar imaging. In this paper, compressive noise radar imaging is experimentally shown to be feasible for urban sensing applications. S-band through-the-wall imaging results demonstrate the feasibility of using compressive noise radar for sensing obscured targets of interest in urban scenarios.

关键词： Radar imaging Imaging sensors signal to noise ratio Ultra wideband radar

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A Graph Autoencoder Approach to Crowdsourcing

A Graph Autoencoder Approach to Crowdsourcing

引用

sensor array and multichannel signal processing workshop

作者： Panagiotis A. Traganitis Charilaos I. Kanatsoulis Dept. of Electrical and Computer Engineering Michigan State University East Lansing MI USA Dept. of Computer Science Stanford University Palo Alto CA USA

ISBN: (数字)9798350344813

ISBN: (纸本)9798350344820

Crowdsourcing deals with combining and aggregating labels from crowds of annotators of unknown reliability. While most works on label aggregation operate under the assumption of independent and identically distributed data, the present work introduces an algorithm that operates under known data dependencies or correlations. To exploit these dependencies, a novel graph autoencoder-based algorithm is developed that fuses annotator labels for crowdsourced classification tasks. Numerical tests on real data showcase the potential of the proposed approach.

关键词： Crowdsourcing Correlation Fuses Conferences signal processing algorithms Distributed databases Classification algorithms

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Revisiting semi-supervised training objectives for differentiable particle filters

Revisiting semi-supervised training objectives for different...

引用

sensor array and multichannel signal processing workshop

作者： Jiaxi Li John-Joseph Brady Xiongjie Chen Yunpeng Li Computer Science Research Centre University of Surrey Guildford United Kingdom

ISBN: (数字)9798350344813

ISBN: (纸本)9798350344820

Differentiable particle filters combine the flexibility of neural networks with the probabilistic nature of sequential Monte Carlo methods. However, traditional approaches rely on the availability of labelled data, i.e., the ground truth latent state information, which is often difficult to obtain in real-world applications. This paper compares the effectiveness of two semi-supervised training objectives for differentiable particle filters. We present results in two simulated environments where labelled data are scarce.

关键词： Training Monte Carlo methods Conferences Neural networks signal processing algorithms Performance gain Probabilistic logic

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Optimal Adaptive array and Angle Tracking for Multiple Targets - A Re-examination of Optimal array processing

Optimal Adaptive Array and Angle Tracking for Multiple Targe...

引用

sensor array and multichannel signal processing workshop

作者： Huaijin Gu Louisiana Tech University USA

ISBN: (纸本)1424403081

The optimal array for detecting the signal from a desired direction but contaminated by receiver noise and strong interference from different sources with unknown arriving-angles is re-examined. The well-known optimal array is obtained by inverting the covariance matrix of interference and noise to maximize the signal to interference and noise ratio (SINR). In practice, the covariance matrix is unknown and has to be estimated by a sample covariance matrix. The optimal array is thus estimated by inverting the sample covariance matrix. This procedure has been employed in optimal array research without challenge. However, it is shown in this paper that the estimated optimal array fails to yield the highest SINR in the case of unknown arriving-angles. Instead the highest SINR can be achieved by optimally estimating the arriving-angles of interference followed by a constrained matched filter, which maximizes the signal to noise ratio subject to canceling the interference from the estimated arriving-angles. In order to reduce the computational burden, an angle-tracking system for multiple targets is adopted to achieve the optimal estimation of arriving-angles. The resulting system of angle-tracking adaptive array offers the highest SINR at a computational burden only on 2 the order of N middot M 2 multiplications within a radar range-cellDeltatau, rather than N 3 multiplications in the well-known but questionable estimated optimal array. Here N is the number of sensors in the array and M the number of interference sources. Typically, N = 1,000 in a planar radar array, M = 2-10 and Deltatau = 1 mus. Numerical simulations confirm the theoretical results

关键词： Adaptive arrays Target tracking array signal processing signal to noise ratio Interference Covariance matrix sensor arrays Radar tracking signal detection Yield estimation

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Calibration of Polarimetric Antenna arrays Using Neural Networks

Calibration of Polarimetric Antenna Arrays Using Neural Netw...

引用

sensor array and multichannel signal processing workshop

作者： Jannik Springer Philipp Mikus Marc Oispuu Wolfgang Koch Peter Knott Fraunhofer Institute for Communication Information Processing and Ergonomics FKIE Wachtberg Germany Fraunhofer Institute for High Frequency Physics and Radar Techniques FHR Wachtberg Germany

ISBN: (数字)9798350344813

ISBN: (纸本)9798350344820

This paper addresses the problem of calibration for antenna arrays with multi-port polarimetric elements. Model-based array signal processing techniques require an accurate model of the complex array response and model errors can, for example, cause significant systematic direction finding errors. Modeling the response of polarimetric antenna arrays can be particularly challenging due to cross-polarization and mutual coupling effects in the multi-port antenna elements. This work proposes a new calibration technique for polarimetric antenna arrays using neural networks that learn any mismatches between the modeled and the actual array response. The technique is evaluated based on the measured response of a five-element dual-polarized antenna array and outperforms conventional calibration techniques like mutual coupling calibration or local polynomial approximation. Its performance is studied exemplarily for the direction finding problem.

关键词： Antenna measurements Training Direction-of-arrival estimation Systematics array signal processing Artificial neural networks Parallel processing

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Direct Position Determination of Locally Scattered Sources Using Generalized array Manifold Model

Direct Position Determination of Locally Scattered Sources U...

引用

sensor array and multichannel signal processing workshop

作者： Devan Palur Palanivelu Marc Oispuu Wolfgang Koch Thomas Dallmann Fraunhofer Institute for Communication Information Processing and Ergonomics FKIE Wachtberg Germany Radio Technologies for Automated and Connected Vehicles Research Group Technische Univcrsität Ilmenau Germany

ISBN: (数字)9798350344813

ISBN: (纸本)9798350344820

Source localization from raw array data by repa-rameterizing the array steering vector by the source position is a fundamental principle of direct position determination (DPD). In this paper, we propose a DPD method to estimate the position of locally scattered sources using an unsynchronized array sensor network. Here, we use the well-known generalized array manifold (GAM) model which approximates the steering vector using its first-order gradient in order to characterize the local scattering effect. The proposed method is compared with the conventional two-stage bearings-only localization (BOL) approach. Simulation results reveal that the proposed DPD position estimates asymptotically attain the derived Cramér-Rae Bound (CRB) for high SNR values and an improved localization accuracy is achieved by exploiting the local scattering parameters in the localization.

关键词： Location awareness Manifolds Accuracy Systematics array signal processing Scattering Vectors

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Energy profiling of FPGA-based PHY-layer building blocks encountered in modern wireless communication systems

Energy profiling of FPGA-based PHY-layer building blocks enc...

引用

sensor array and multichannel signal processing workshop

作者： Nikolaos Bartzoudis Oriol Font-Bach Miquel Payaró Antonio Pascual-Iserte Javier Rubio Juan José García Fernández Ana García Armada Centre Tecnològic de Telecomunicacions de Catalunya (CTTC) Castelldefels Spain Dept. Signal Theory and Communications Universitat Politècnica de Catalunya (UPC) Barcelona Spain Dept. Signal Theory and Communications Universidad Carlos III de Madrid (UC3M) Madrid Spain

Characterizing the energy cost of different physical (PHY) layer building blocks is becoming increasingly important in modern cellular-based communications, considering the cross sector requirements for performance enhancements and energy savings. This paper presents energy profiling metrics of different PHY-layer FPGA implementations encountered in modern wireless communication systems. The results give an insight of the distribution of the consumed energy in different baseband building blocks or configurations before and after applying power optimizations in the FPGA design and implementation.

关键词： Field programmable gate arrays WiMAX Power demand Optimization Receivers Standards Measurement

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NEMO: Internet of Things based Real-time Noise and Emissions MOnitoring System for Smart Cities

NEMO: Internet of Things based Real-time Noise and Emissions...

引用

sensor array and multichannel signal processing workshop

作者： Ashish Rauniyar Truls Berge Jan Erik Hå kegå rd Sustainable Communication Technologies Group SINTEF Digital Norway

With the advent of ubiquitous sensors and Internet of Things (IoT) applications, research and development initiatives on smart cities are ramping up worldwide. It enables remote monitoring, management, and control of devices and the generation of fresh and actionable insight from huge quantities of real-time data. Real-time noise and emissions monitoring of vehicles remain indispensable in a smart city context. Effective management and control of noise and emissions of vehicles on the road are necessary and possible through analyzing lots of sensor data in real-time to take an actionable insight. To contribute to this, as part of an ongoing effort of the European Union project called “NEMO: Noise and Emissions Monitoring and Radical Mitigation”, in this paper, we present the design and development of an IoT-based real-time noise and emissions monitoring system for vehicles in a smart city context. Real-world sensor data of the vehicles in some European cities are collected during the pilot tests. We have developed a complete application for infrastructure managers and analysts to monitor the sensor data related to noise and emissions of vehicles in real-time. The data of the individual road vehicles and trains in selected EU cities and from trains on a track in the Netherlands are collected in the cloud and analyzed with artificial intelligence (AI) algorithms for classification such as high emitter, medium emitter, and normal emitters. We present the development of a complete software solution that can be integrated with existing intelligent transportation systems in smart cities. Finally, we report the initial vehicle classification results from the Rotterdam (Netherlands) pilot test as a representative example for the NEMO monitoring system.

关键词： Smart cities Software algorithms Europe Real-time systems Software Internet of Things Artificial intelligence

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Multi-Tier Structured array for Sensing Pilot Design in Integrated Sensing and Communication

Multi-Tier Structured Array for Sensing Pilot Design in Inte...

引用

sensor array and multichannel signal processing workshop

作者： Jiaying Ren Shawn Tsai Advanced Communication Technology Communication System Design Mediatek USA Inc San Diego CA USA

ISBN: (数字)9798350344813

ISBN: (纸本)9798350344820

In this paper, we explore the use of large-scale sparse arrays for pilot placement in pilot-based sensing within integrated sensing and communication (ISAC) systems. Unlike conventional regular pilot placement method, sparse placement offers a significant reduction in overhead while maintaining high sensing performance. We present a novel large-scale sparse array construction method by introducing a multi-tier array structure. Using the proposed method, the design of large-scale sparse arrays can be simplified into several smaller-sized array design problems, significantly reducing computational complexity and storage requirements. Numerical examples demonstrate the effectiveness of the proposed method for low-overhead sensing pilot placement design, which is applicable in future 6G applications.

关键词： 6G mobile communication array signal processing Design methodology Conferences Integrated sensing and communication Frequency division multiplexing Computational complexity

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