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A Unified Multi-Functional Dynamic Spectrum Access Framework: Tutorial, Theory and Multi-GHz Wideband Testbed

Robert Qiu, Nan Guo, Husheng Li, Zhiqiang Wu, Vasu Chakravarthy, Yu Song, Zhen Hu, Peng Zhang, Zhe Chen
2009 Sensors  
) multi-GHz front end, (4) compressed sensing for multi-GHz waveforms-revolutionary A/D, (5) machine learning for cognitive radio/radar, (6) quickest detection, and (7) overlay/underlay cognitive radio  ...  The goal of this paper is a tutorial treatment of wideband cognitive radio and radar-a convergence of (1) algorithms survey, (2) hardware platforms survey, (3) challenges for multi-function (radar/communications  ...  the status of channel and recognizing the extracted feature parameters).  ... 
doi:10.3390/s90806530 pmid:22454598 pmcid:PMC3312458 fatcat:3hljqkjzxvgpfh5vue5gbdk65q

RADAR 2019 Author Index

2019 2019 International Radar Conference (RADAR)  
Stefan Training Data Selection Strategy for CFAR Ship Detection in Range-Compressed Radar Data submission_35 BEER Stefan Weather Mode Pulse Compression Design for an Airborne Sense & Avoid Radar  ...  PRALON Leandro FPGA Design and Implementation of a Real-time Subpulse Processing Architecture for Noise Radars submission_314 PRALON Mariana FPGA Design and Implementation of a Real-time Subpulse  ... 
doi:10.1109/radar41533.2019.9078992 fatcat:qgj7mi5yrfc7ti5qz6he5n4xvm

Multiclass Radio Frequency Interference Detection and Suppression for SAR Based on the Single Shot MultiBox Detector

Junfei Yu, Jingwen Li, Bing Sun, Jie Chen, Chunsheng Li
2018 Sensors  
Next, the timefrequency dataset acts as input data to train the SSD and obtain a network that is capable of detecting, identifying and estimating the interference.  ...  First, an echo-interference dataset is established by randomly combining the target signal with various types of RFI in a simulation, and the timefrequency form of the dataset is obtained by utilizing  ...  Conflicts of Interest: The authors have no conflict of interest to declare.  ... 
doi:10.3390/s18114034 pmid:30463243 fatcat:6xufdifgnzfidjuxehtck33oay

Optimal Defect Detection and Sensing System of Railway Tunnel Radar considering Multisensor System Combined with Active Interference Suppression Algorithm

Yang Lei, Yong Zou, Bo Jiang, Tian Tian, Daqing Gong
2022 Computational Intelligence and Neuroscience  
This article analyzes several factors that affect the radar detection effect and makes a detailed summary from the detection environment and other aspects.  ...  Radar detectors have the advantages of losslessness, high efficiency, high resolution, and high-speed radar image capture.  ...  Each narrowband interference is independent of each other. ere are different frequency points in the interference center, and spectrum interference can produce narrowband interference at multiple different  ... 
doi:10.1155/2022/2459996 pmid:35510062 pmcid:PMC9061014 fatcat:xq7cambhjnfrrlssbnhwzjjyc4

Grand Challenges in Radar Signal Processing

Fulvio Gini
2021 Frontiers in Signal Processing  
ACKNOWLEDGMENTS The author wish to thank Moeness Amin, Antonio De Maio, Alessio Balleri, and Fabiola Colone for reading the manuscript and providing very useful comments.  ...  GRAND CHALLENGES IN RADAR SIGNAL PROCESSING Sparse Sensing and Sparse Array Design in Radar Sparse sensing, or compressed sensing (CS), has been successful in solving the problems of target detection  ...  Micro-Doppler Radar A moving point-like target introduces a frequency shift in the narrowband radar return due to the Doppler effect.  ... 
doi:10.3389/frsip.2021.664232 fatcat:ekjgx65rhrgxdciw2zhb5bqmqq

Joint multiband signal detection and cyclic spectrum estimation from compressive samples

Lebing Pan, Shiliang Xiao, Xiaobing Yuan, Baoqing Li
2014 EURASIP Journal on Wireless Communications and Networking  
Based on the results of the first step, parameter extraction from the cyclic spectrum is performed by searching for peaks rather than by setting a threshold.  ...  This paper focuses on wide-sense stationary signal processing within a compressive sensing framework, proposing a new method of compressive sampling fast Fourier transform (FFT) accumulation method (CS-FAM  ...  The output of the first step in CS-FAM is derived by (11) 3 Joint signal processing from compressive samples In this article, multiband detection and parameter extraction are performed in the frequency  ... 
doi:10.1186/1687-1499-2014-218 fatcat:mah2jdmp45elvl4yohptammmam

A New Direction for Biosensing: RF Sensors for Monitoring Cardio-Pulmonary Function [chapter]

Ju Gao, Siddharth Baskar, Diyan Teng, Mustafa al'Absi, Santosh Kumar, Emre Ertin
2017 Mobile Health  
retrieving features and statistics of clinical significance.  ...  In this chapter, we review advances in a novel sensing modality using radio frequency (RF) waves that can provide physiological measurements without skin contact in both lab and field environments.  ...  EasySense GLRT statistics, (b) Comparison of RR intervals extracted from ECG and EasySense measurements Fig. 9 9 HRV energy spectrum computed using the Welch's periodogram each time slot t, we calculate  ... 
doi:10.1007/978-3-319-51394-2_15 fatcat:z3n4ejub3fgaxevb33esfml26a

Signal Detection in a Nonstationary Environment Reformulated as an Adaptive Pattern Classification Problem [chapter]

2009 Intelligent Signal Processing  
Time, an essential dimension of learning, appears explicitly in the dynamic spectrum and Wigner-Ville distribution and implicitly in the Loève spectrum.  ...  From this principled discussion, three important tools emerge: the dynamic spectrum, the Wigner-Ville distribution as an instantaneous estimate of the dynamic spectrum, and the Loève spectrum.  ...  Currie for reading the final version of the paper and providing comments.  ... 
doi:10.1109/9780470544976.ch13 fatcat:74dap72dune3rit7umuw53hxla

Towards a Cognitive Radar: Canada's Third-Generation High Frequency Surface Wave Radar (HFSWR) for Surveillance of the 200 Nautical Mile Exclusive Economic Zone

Anthony Ponsford, Rick McKerracher, Zhen Ding, Peter Moo, Derek Yee
2017 Sensors  
Cognitive sense-and-adapt technology and dynamic spectrum management ensures robust and resilient operation in the highly congested High Frequency (HF) band.  ...  Dynamic spectrum access enables the system to simultaneously operate on two frequencies on a non-interference and non-protected basis, without impacting other spectrum users.  ...  A feature extraction algorithm is then designed to extract features from a continuous string of signature signals that are commensurate with the targets of interest being tracked over time.  ... 
doi:10.3390/s17071588 pmid:28686198 pmcid:PMC5539545 fatcat:rnc3nbekm5gb3k5bmd2kspd664

Wideband Cognitive Radio Networks Based Compressed Spectrum Sensing: A Survey

Mohammed Asaduzzaman Abo-Zahhad, Sabah M. Ahmed, Mohammed Asaduzzaman Farrag, Khaled Ali BaAli
2018 Journal of Signal and Information Processing  
The task of sensing is becoming more challenging especially at wideband spectrum scenario.  ...  In this paper, we discuss the approaches used for solving compressed spectrum sensing problem for wideband cognitive radio networks and how the problem is formulated and rendered to improve the detection  ...  In detection, we do not ever reconstruct the signal rather than extract sufficient statistics from a small number of random projections or compressive measurements from the frequency band under observation  ... 
doi:10.4236/jsip.2018.92008 fatcat:uxre4m3lfzcqpkvlbeokm33rou

2019 Index IEEE Transactions on Geoscience and Remote Sensing Vol. 57

2019 IEEE Transactions on Geoscience and Remote Sensing  
., and Drake, V.A., Insect Biological Parameter Estimation Based on the Invariant Target Parameters of the Scattering Matrix; TGRS Aug. 2019 6212-6225 Hu, C., see Zhang, M., TGRS Sept. 2019 6666-6674  ...  on Arbitrary Region of Interest; TGRS Oct. 2019 7995-8010 Hu, T., see Kang, Z., TGRS Jan. 2019 181-193 Hu, T., Wu, Y., Zheng, G., Zhang, D., Zhang, Y., and Li, Y., Tropical Cyclone Center  ...  ., +, TGRS Jan. 2019 395-405 Feature extraction 3-D Gaussian-Gabor Feature Extraction and Selection for Hyperspectral Imagery Classification.  ... 
doi:10.1109/tgrs.2020.2967201 fatcat:kpfxoidv5bgcfo36zfsnxe4aj4

20 Years of Evolution from Cognitive to Intelligent Communications [article]

Zhijin Qin, Xiangwei Zhou, Lin Zhang, Yue Gao, Ying-Chang Liang, and Geoffrey Ye Li
2019 arXiv   pre-print
Particularly, this article starts from a comprehensive review of typical spectrum sensing and sharing, followed by the recent achievements on the AI-enabled intelligent radio.  ...  To improve the spectrum efficiency, CR enables unlicensed usage of licensed spectrum resources. It has been regarded as the key enabler for intelligent communications.  ...  Fig. 2 . 2 Comparison of narrowband and wideband spectrum sensing based on compressive sensing.  ... 
arXiv:1909.11562v1 fatcat:au2oewpfm5eb3ccnnpvrcbypim

Mitigation of Radio Frequency Interference in Synthetic Aperture Radar Data: Current Status and Future Trends

Mingliang Tao, Jia Su, Yan Huang, Ling Wang
2019 Remote Sensing  
From the view of spectrum allocation, possible terrestrial and spaceborne RFI sources to SAR system and their geometry are analyzed.  ...  Radio frequency interference (RFI) is a major issue in accurate remote sensing by a synthetic aperture radar (SAR) system, which poses a great hindrance to raw data collection, image formation, and subsequent  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/rs11202438 fatcat:7mlqnrz725afnoja4sksnoladu

Signal detection in a nonstationary environment reformulated as an adaptive pattern classification problem

S. Haykin, D.J. Thomson
1998 Proceedings of the IEEE  
Time, an essential dimension of learning, appears explicitly in the dynamic spectrum and Wigner-Ville distribution and implicitly in the Loève spectrum.  ...  From this principled discussion, three important tools emerge: the dynamic spectrum, the Wigner-Ville distribution as an instantaneous estimate of the dynamic spectrum, and the Loève spectrum.  ...  Currie for reading the final version of the paper and providing comments.  ... 
doi:10.1109/5.726792 fatcat:d3lncq3vnzgthocp6k5x3n5vva

Table of Contents

2021 IEEE Transactions on Signal Processing  
Sayed Third-Order Statistics Reconstruction From Compressive Measurements . . . . . . . . . . . . . . . . . . . . . . . . . Y. Wang and Z.  ...  Li Robust Spectrum Sensing Via Probability Measure Transform . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Y. Sorek and K.  ... 
doi:10.1109/tsp.2021.3136798 fatcat:kzkdhzcz3fgx3jv6gfjofooseq
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