Adaptive False-Target Recognition for the Proximity Sensor Based on Joint-Feature Extraction and Chaotic Encryption

Dai, Jian; Hao, Xinhong; Yan, Xiaopeng; Li, Ze

doi:10.1109/jsen.2022.3169746

Cited by 9 publications

(4 citation statements)

References 29 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%

“…Simulation experiments were also carried out to demonstrate the superiority of the averaged range sidelobe method. Dai et al [12] proposed three different false-target recognition strategies for different kinds of interference, and dynamically allocated the three false-target recognition strategies based on the maximized payoff principle in the non-cooperative game between the radio frequency proximity sensor and the interference, which can significantly improve the falsetarget recognition performance of the radio frequency proximity sensor. A small sample terrain recognition framework [13] based on the carrier-free UWB proximity sensor was proposed to classify terrain echo signals using time-frequency feature maps.…”

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 application of image processing is widespread across various computer systems [1,2], and the domain of cryptography has been enriched by the assimilation of novel technologies and conceptual paradigms. These advancements pertain to domains such as information theory [3], quantum computing [4], neural networks [5], Very Large Scale Integration (VLSI) technology [6], and, notably, chaos theory [7]. The intersection of image encryption with chaos theory is particularly salient and forms the crux of the ensuing discourse.…”

Section: Introductionmentioning

confidence: 99%

Chaotic Map Based Raster Data Encryption for Geospatial Data

Bhangale,

Vaikole

2023

IJSSE

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Data confidentiality, security authentication are just some of the many uses for image encryption, making it one of the most effective methods for safeguarding geospatial data. However, even with advancements in an encryption algorithms still face challenges in terms of both security and speed. However, limitations in key space, complexity of algorithms, make it susceptible to assaults plague present in image encryption methods. Considering the restrictions of past strategies, we've formulated a brought together way to deal with raster data encryption by consolidating shuffled raster Output, Chirikov and Chebyshev chaotic map. At the point image is the constant raster is first shuffled by shuffling method to muddle the pixels of each block. The randomization characteristic in keys generated by Chirikov and Chebyshev Chaotic maps will be used to encode raster data. Encryption is performed rapidly utilizing the recommended approach. The reenactment results exhibit the adequacy and reasonableness of the method for safeguarding raster geospatial data.

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“…In recent years, the cryptography research community has taken advantage of the advancements in different technologies and theories including information theory [7], quantum computing [8], neural computing [9], Very Large Scale Integration (VLSI) technology [10], and especially, chaos theory [11].…”

Section: Introductionmentioning

confidence: 99%

Chaotic Image Encryption: State-of-the-Art, Ecosystem, and Future Roadmap

Zolfaghari

Koshiba

2022

ASI

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Recently, many researchers have been interested in the application of chaos in cryptography. Specifically, numerous research works have been focusing on chaotic image encryption. A comprehensive survey can highlight existing trends and shed light on less-studied topics in the area of chaotic image encryption. In addition to such a survey, this paper studies the main challenges in this field, establishes an ecosystem for chaotic image encryption, and develops a future roadmap for further research in this area.

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Adaptive False-Target Recognition for the Proximity Sensor Based on Joint-Feature Extraction and Chaotic Encryption

Cited by 9 publications

References 29 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

Chaotic Map Based Raster Data Encryption for Geospatial Data

Chaotic Image Encryption: State-of-the-Art, Ecosystem, and Future Roadmap

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