A novel SINR and mutual information based radar jamming technique

Wang, Lulu; Wang, Hongqiang; Cheng, Yongqiang; Qin, Yuliang

doi:10.1007/s11771-013-1871-6

Cited by 10 publications

(13 citation statements)

References 12 publications

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“…With the development of electronic countermeasure technology, waveform design presents a need to solve radar interference issues. In [ 16 , 17 ], the technique from [ 11 ] was extended to a target defense application, and task-dependent, power-constraint, optimal jamming techniques were investigated; the main goal was to minimize the MI between the radar echoes and the stochastic target impulse response. In addition, the waveform strategy design problem for the jammer based on MI was considered in [ 18 ].…”

Section: Introductionmentioning

confidence: 99%

Information–Theoretic Radar Waveform Design under the SINR Constraint

Xiao

Deng

2020

Entropy

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This study investigates the information–theoretic waveform design problem to improve radar performance in the presence of signal-dependent clutter environments. The goal was to study the waveform energy allocation strategies and provide guidance for radar waveform design through the trade-off relationship between the information theory criterion and the signal-to-interference-plus-noise ratio (SINR) criterion. To this end, a model of the constraint relationship among the mutual information (MI), the Kullback–Leibler divergence (KLD), and the SINR is established in the frequency domain. The effects of the SINR value range on maximizing the MI and KLD under the energy constraint are derived. Under the constraints of energy and the SINR, the optimal radar waveform method based on maximizing the MI is proposed for radar estimation, with another method based on maximizing the KLD proposed for radar detection. The maximum MI value range is bounded by SINR and the maximum KLD value range is between 0 and the Jenson–Shannon divergence (J-divergence) value. Simulation results show that under the SINR constraint, the MI-based optimal signal waveform can make full use of the transmitted energy to target information extraction and put the signal energy in the frequency bin where the target spectrum is larger than the clutter spectrum. The KLD-based optimal signal waveform can therefore make full use of the transmitted energy to detect the target and put the signal energy in the frequency bin with the maximum target spectrum.

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Section: Introductionmentioning

confidence: 99%

Information–Theoretic Radar Waveform Design under the SINR Constraint

Xiao

Deng

2020

Entropy

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“…It can describe linear correlations and non-linear correlations. It is widely used in variable selection [12,16,17]. The mutual information Mi(A, B) is defined as follows:…”

Section: Mutual Informationmentioning

confidence: 99%

Automatic extraction of Uyghur domain concepts based on multi‐feature for ontology extension

et al. 2020

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In the internet age, as a conceptual model of knowledge organisation, ontology has become a research hotspot. Ontology extension achieves the purpose of expanding ontology by adding new concepts and discovering the relationships between concepts in the existing ontology. In order to improve the automation and accuracy of ontology concept extraction in the Uyghur language, here the authors propose a new method to automatically extract concepts from text collection. For the characteristics of the Uyghur domain ontology concept, the text preprocessing is performed first, then the inter-word correlation of multi-feature fusion is calculated, such as Mi, Cd and Ea, and finally, the domain terminology and concept are automatically extracted, according to the term frequency-inverse document frequency algorithm. Experiment results show that, in terms of precision and recall rate, the multi-feature method proposed here represents an improvement over other methods. It also proves the feasibility and effectiveness of the authors' method to extract the domain concept.

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“…Furthermore, reference Deligiannis et al (2016) adopts game theory to tackle the problem of competitive power allocation for MIMO radar in the presence of multiple jammers, the main objective of the radar system is to guarantee a desired target detection performance utilizing the minimum transmission power, while the intelligent jammers optimize the jamming power to maximize the interference to the radars. In Wang et al (2013), the SINR-and MI-based jamming design algorithms are presented to protect the target from detection and estimation, respectively. However, the precise characteristics of radar waveform is impossible to estimate in practice.…”

Section: Radio Sciencementioning

confidence: 99%

“…Recently, the electromagnetic environment of modern warfare is becoming much more complex, which has brought up the problem of investigating the interaction between radar and target (L. L. Wang et al, , ). In general, the open literature is now rich with a number of studies, which concentrate on waveform design to improve the performance of radar system.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Jamming Waveform Design for Distributed Multiple‐Radar Architectures Based on Low Probability of Intercept

et al. 2019

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This paper investigates the problem of low probability of intercept (LPI)‐based adaptive jamming waveform design for distributed multiple‐radar architectures. Such a smart jammer system adopts a multibeam working mode, where multiple simultaneous jamming beams are synthesized to interfere with multiple radars independently. The primary objective of the smart jammer is to minimize the total jamming power by optimizing the transmitted jamming waveform while the achieved signal‐to‐interference‐plus‐noise ratio (SINR) and mutual information (MI) between the received echoes from the target at each radar receiver and the target impulse responses are enforced to be below specified thresholds. First, the expressions of SINR and MI are derived to characterize target detection and characterization performance, respectively. Then, two different LPI‐based jamming waveform design strategies are proposed to minimize the total noise jamming power by optimizing the jamming waveform while the achieved SINR/MI is enforced to be below a certain threshold. The resulting optimization problems are solved analytically by employing the technique of Lagrange multipliers. With the aid of some numerical examples, it is illustrated that the two schemes result in different jamming waveform design results, which is useful to guide jamming power allocation for various jamming tasks. It is also shown that the LPI performance of the smart jammer can be efficiently improved by exploiting the proposed jamming waveform design criteria.

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A novel SINR and mutual information based radar jamming technique

Cited by 10 publications

References 12 publications

Information–Theoretic Radar Waveform Design under the SINR Constraint

Information–Theoretic Radar Waveform Design under the SINR Constraint

Automatic extraction of Uyghur domain concepts based on multi‐feature for ontology extension

Adaptive Jamming Waveform Design for Distributed Multiple‐Radar Architectures Based on Low Probability of Intercept

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