Results 21 to 30 of about 2,161,885 (199)

The dependence of radar target detectability on array weighting function [PDF]

, 2009
Presented at the IET-Radar 2007 Conference Edinburgh 15-18 October 2007This paper describes simulation work to assess the detectability of targets by an airborne fire control radar (FCR) operating in a medium pulse repetition frequency (PRF) mode in ...
Alabaster, Clive M., Hughes, Evan J.
core   +7 more sources

Developments in target micro-Doppler signatures analysis : radar imaging, ultrasound and through-the-wall radar [PDF]

, 2013
Target motions, other than the main bulk translation of the target, induce Doppler modulations around the main Doppler shift that form what is commonly called a target micro-Doppler signature.
Woodbridge, K., Clemente, C., Soraghan, J.J., Balleri, A.   +3 more
core   +5 more sources

A Dual-Modal Wearable PPG Smartwatch with AI-Enhanced Correction for High-Accuracy and Continuous AF Burden Assessment. [PDF]

Adv Sci (Weinh)
ABSTRACT Atrial fibrillation (AF) increases the risk of stroke and heart failure, yet accurate quantification of AF burden in daily life remains difficult. Although smartwatch photoplethysmography (PPG) supports continuous monitoring, complex rhythms and signal noise can impair burden estimation.
Zuo S, Wang J, Wang X, Feng H, Zhao Y, Li F, Wei S, Zhou L, Zhao Z, Chen S, Kong X, Wang J, He L, Xia S, Li X, Zhang J, Liu X, Guo X, Zhou N, Li S, Jiang C, Tang R, Sang C, Long D, Du X, Dong J, Zhu W, Ma C.   +27 more
europepmc   +2 more sources

Waveform Recognition in Pulse Compression Radar Systems [PDF]

2005 IEEE Workshop on Machine Learning for Signal Processing, 2006
In this paper a system for recognizing pulse compression radar waveforms is introduced. The waveforms considered in this study are the linear frequency modulation (LFM), Costas codes, binary phase codes, and the Frank, P1, P2, P3, and P4 codes. A feature vector based on instantaneous signal properties, second- and higher-order statistics, and time ...
J. Lunden, L. Terho, V. Koivunen
openaire   +1 more source

Densely-Accumulated Convolutional Network for Accurate LPI Radar Waveform Recognition

2021 IEEE Global Communications Conference (GLOBECOM), 2021
Abstract This paper presents a deep learning-based method to automatically recognize low probability of intercept (LPI) radar waveforms against diversified jamming attacks. Concretely, an efficient convolutional neural network (CNN) architecture, namely Densely-Accumulated Network (DANet), is introduced to learn the time-frequency representation ...
Thien Huynh-The, Quoc-Viet Pham, Toan-Van Nguyen, Van-Sang Doan, Nhan Thanh Nguyen 0001, Daniel Benevides da Costa, Dong-Seong Kim 0002   +6 more
openaire   +3 more sources

Radar Operation Mode Recognition via Multifeature Residual-and-Shrinkage ConvNet

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023
Radar operation mode recognition holds an increasingly critical place in electronic countermeasure as well as in remote sensing. However, the overlapped waveform parameters pose huge challenges to performing the radar operation mode recognition task in ...
Yujie Zhang, Weibo Huo, Cui Zhang, Yulin Huang, Jifang Pei, Yin Zhang, Jianyu Yang   +6 more
doaj   +1 more source

Extended Target Recognition in Cognitive Radar Networks

Sensors, 2010
We address the problem of adaptive waveform design for extended target recognition in cognitive radar networks. A closed-loop active target recognition radar system is extended to the case of a centralized cognitive radar network, in which a generalized ...
Xiqin Wang, Yimin Liu, Huadong Meng, Yimin Wei   +3 more
doaj   +1 more source

Multidimensional Waveform Encoding for Synthetic Aperture Radar Remote Sensing [PDF]

, 2007
This paper introduces and analyses the innovative concept of multidimensional waveform encoding for spaceborne synthetic aperture radar (SAR). The combination of this technique with digital beamforming on receive enables a new class of highly ...
Moreira, Alberto, A. Moreira, G. Krieger, Gebert, Nicolas, Krieger, Gerhard, N. Gebert   +5 more
core   +1 more source

Radar Sensor Networks: Algorithms for Waveform Design and Diversity with Application to ATR with Delay-Doppler Uncertainty

EURASIP Journal on Wireless Communications and Networking, 2007
Automatic target recognition (ATR) in target search phase is very challenging because the target range and mobility are not yet perfectly known, which results in delay-Doppler uncertainty.
Qilian Liang
doaj   +2 more sources

Radar Waveform Recognition Using Fourier-Based Synchrosqueezing Transform and CNN [PDF]

2019 IEEE 8th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2019
In this paper the problem of recognizing radar waveforms is addressed. Waveform classification is needed in spectrum sharing and radar-communications coexistence, cognitive radars and signal intelligence. Different radar waveforms exhibit different properties in time-frequency domain. We propose a deep learning method for waveform classification.
Koivunen, Visa, Kong, Gyuyeol
openaire   +4 more sources