Hierarchical Dictionary Learning for Vehicle Classification Based on the Carrier-Free UWB Radar

Zhu, Yuying; Zhang, Shuning; Zhu, Lingzhi; Sun, Yuyang; Chen, Si

doi:10.1109/tgrs.2022.3148738

Cited by 5 publications

(3 citation statements)

References 47 publications

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“…Radio fuze output signals process and mainly research the radio fuze output signals' recognition and classification [11][12][13][14][15]. Based on the statistical properties of continuous wave detector outputs under swept jamming, an averaged range flanking method was proposed [11], which uses the fast Fourier transform to extract the harmonic envelope and averages the multiple harmonic coefficients obtained by FFT.…”

Section: Related Workmentioning

confidence: 99%

“…Insufficient samples make the classifier prone to overfitting, so the author proposed an Improved Auxiliary Classifier Generative Adversarial Networks for data enhancement in the paper. Zhu et al [14] proposed a hierarchical dictionary learning mechanism for vehicle recognition based on the carrier-free UWB radar. The hierarchical dictionary learning framework aids the model in learning discriminative representations through reconstructing clean data over the signal dictionary, which encourages the sub-dictionary to be representative for signals from the corresponding category but to be away from other categories.…”

Section: Related Workmentioning

confidence: 99%

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Classification and Identification Method of Radio Fuze Target and Sweep Jamming Signals Based on Third-Order Spectrum Features

et al. 2022

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To overcome the problem of insufficiency of linear frequency modulation (LFM) radio fuzes against sweep-type jamming, a method is proposed to classify and identify radio fuze targets and interfering signals based on third-order spectrum features. Using the measured data of an LFM radio fuze, the third-order spectral transform is applied to the output signals of the detector end under the action of the target and several amplitude modulated sweeping interfering signals, and the amplitude mean value, third-order spectral amplitude entropy, and third-order spectral singular value entropy based on the third-order spectrum are extracted as three-dimensional features. The experimental results show that the classification and identification of targets and AM sweep-type interference using the third-order spectral features of the signal at the detector end has a high success rate, with a comprehensive identification accuracy of 98.33%.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Classification and Identification Method of Radio Fuze Target and Sweep Jamming Signals Based on Third-Order Spectrum Features

et al. 2022

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“…The seismic data provides direct insights into various structural aspects, such as the shape of stratigraphic interfaces, burial depth, and other structural features [2]. This structural information is highly valuable and serves as a fundamental resource for seismic exploration since its inception [3]. Extracting structural information from seismic data has become a vital objective in seismic exploration [4].…”

Section: Introductionmentioning

confidence: 99%

Development of an automatic tracking model for seismic stratigraphic correlation based on information entropy theory

Du,

Guo,

Liu

et al. 2023

HSET

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Accurate stratigraphic information is the basis of seismic data interpretation and reserve prediction. Based on this, this paper firstly establishes a grey model based on information entropy, uses particle swarm optimization technology of neural network to analyze and track the influence of each factor on the degree of seismic hazards, and gets the weight of each factor on the degree of occurrence of geologic hazards through the model by using the matlab software, and secondly, uses the theory of information entropy to determine the evaluation system and its grading standard, and finally evaluates the comprehensive evaluation of fuzzy through the grey clustering model. bp neural network. The development and research of automatic tracking model of seismic stratigraphic correlation based on information entropy theory can greatly improve the efficiency and accuracy of seismic data interpretation, which is of practical value and significance for seismic data interpretation.

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Spectrum sensing based on delayed coprime sampling

Hou

Zhu²,

Zhu³

et al. 2022

Digital Signal Processing

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Hierarchical Dictionary Learning for Vehicle Classification Based on the Carrier-Free UWB Radar

Cited by 5 publications

References 47 publications

Classification and Identification Method of Radio Fuze Target and Sweep Jamming Signals Based on Third-Order Spectrum Features

Classification and Identification Method of Radio Fuze Target and Sweep Jamming Signals Based on Third-Order Spectrum Features

Development of an automatic tracking model for seismic stratigraphic correlation based on information entropy theory

Spectrum sensing based on delayed coprime sampling

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