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A Comprehensive Survey of Machine Learning Applied to Radar Signal Processing
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<span title="2020-09-29">2020</span>
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arXiv
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This work is amply introduced by providing general elements of ML-based RSP and by stating the motivations behind them. ...
Traditional radar signal processing (RSP) methods have shown some limitations when meeting such requirements, particularly in matters of target classification. ...
The classifiers of HRRP-based classification mainly include SVMs [524] , [525] , DBNs [517] , [518] , SAEs [520] , [532] , and RNNs [528] . ...
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Deep-Learning for Radar: A Survey
<span title="">2021</span>
<i title="Institute of Electrical and Electronics Engineers (IEEE)">
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proposed four algorithms to misguide multi-layer perceptron (MLP) and CNN designed for radar ATR using HRRP. ...
SVM), by which a classification rate of 97%-100% had been reached, it has been shown in some papers that the ATR performance of the algorithms trained/tested merely on the MSTAR dataset usually degrade ...
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Table of Contents
<span title="">2020</span>
<i title="IEEE">
2020 IEEE 4th Information Technology, Networking, Electronic and Automation Control Conference (ITNEC)
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Study on Corn Disease Identification Based on PCA and SVM 661 Zixi Liu, Zhixiong Du, Yue Peng, Ming Tong, Xiaoyu Liu, Weicong Chen Wu, C.W. Yuan, R.X. Yin, Wei Sun, W.J. ...
Zhang 158 Multi-scenes Image Stitching Based on Autonomous Driving 694 Lang Wang, Wen Yu, Bao Li 159 Receiving Technology of Multi-target TT&C Signals Using The Unique PRN Code 699 Wenwen Si,Hao Huan 163 ...
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Comparative Analysis of Radar Cross Section Based UAV Classification Techniques
[article]
<span title="2021-12-17">2021</span>
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arXiv
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For example, the classification tree ML achieves an accuracy of 98.66% at 3 dB SNR using the 15 GHz VV-polarized RCS test data from the UAVs. ...
On average, the accuracy of the classification tree ML model performed better than the other algorithms, followed by the Peter Swerling statistical models and the discriminant analysis ML model. ...
THE CLASSIFICATION ALGORITHMS ARE 1: GMM, 2: GAMMA, 3: GPD, 4: SWERLING 1 AND 2, 5: SWERLING 3 AND 4, 6: KNN, 7: SVM, 8: ENSEMBLE, 9: NAIVE BAYES, 10: CLASSIFICATION TREE, 11: DISCRIMINANT ANALYSIS, 12 ...
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Automatic Target Recognition in Synthetic Aperture Radar Imagery: A State-of-the-Art Review
<span title="">2016</span>
<i title="Institute of Electrical and Electronics Engineers (IEEE)">
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This is couched in terms of a single-channel SAR, and it is extendable to multi-channel SAR systems. ...
SVMs are motivated by similar considerations but for nonlinear cases. ...
Depending on the level of polarization complexity supported, the image produced by the SAR system can be any of (1) single polarized, meaning that the SAR sensor only supports a single polarization from ...
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Program
<span title="">2019</span>
<i title="IEEE">
2019 International Conference on Control, Automation and Information Sciences (ICCAIS)
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Target classification is implemented through the data match and correlation of observed HRRP with predicted HRRPs. ...
Finally, different ensemble strategies are carried out and their classification accuracies are compared. ...
accuracy of counting people in cab by 94.1%, and the accuracy of abnormal events detected in cab by 92.2% and 91.7%. pp. 510-515 ...
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Research Advancements in Key Technologies for Space-Based Situational Awareness
<span title="2022-06-18">2022</span>
<i title="American Association for the Advancement of Science (AAAS)">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/rg6zjwpe4zdsdayxrxs6nsffmy" style="color: black;">Space Science & Technology</a>
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Acknowledgments This work was supported by the National Natural Science Foundation of China (Grant No. 11972182), funded by the Science and Technology on Space Intelligent Control Laboratory (Grant Nos ...
The Fourier transform and classification contributed to desired identification results. It is much superior to the HRRP in fine architecture information of the targets. ...
An ensemble learning algorithm of boosting trees was developed for error modeling and prediction. ...
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