Robust Waveform Design Based on Jammer Games in Cognitive Radar

Wang, Bin; Chen, Xu; Li, Shumin; Xin, Fengming; Wang, Jinkuan

doi:10.1109/icccas.2018.8769178

Cited by 2 publications

(5 citation statements)

References 8 publications

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“…Let ε 0 � 1, so with total energy X max � 5, you can distribute 0, 1, 2, 3, 4, or 5 units of energy to x(1), x (2), x (3), or x (4).…”

Section: Maximum Marginal Allocationmentioning

confidence: 99%

“…Related applications and nonlinear methods for robust signal detection and robust estimation are also studied. In [4], considering the uncertainty of the prior information of the radar target in the actual scene, the authors propose a waveform design method based on mutual information to ensure the parameter estimation performance of complex target models.…”

Section: Introductionmentioning

confidence: 99%

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Robust Waveform Design Based on Bisection and Maximum Marginal Allocation Methods with the Concept of Information Entropy

Wang

Hao

2020

Mathematical Problems in Engineering

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Cognitive radar can overcome the shortcomings of traditional radars that are difficult to adapt to complex environments and adaptively adjust the transmitted waveform through closed-loop feedback. The optimization design of the transmitted waveform is a very important issue in the research of cognitive radar. Most of the previous studies on waveform design assume that the prior information of the target spectrum is completely known, but actually the target in the real scene is uncertain. In order to simulate this situation, this paper uses a robust waveform design scheme based on signal-to-interference-plus-noise ratio (SINR) and mutual information (MI). After setting up the signal model, the SINR and MI between target and echo are derived based on the information theory, and robust models for MI and SINR are established. Next, the MI and SINR are maximized by using the maximum marginal allocation (MMA) algorithm and the water-filling method which is improved by bisection algorithm. Simulation results show that, under the most unfavorable conditions, the robust transmitted waveform has better performance than other waveforms in the improvement degree of SINR and MI. By comparing the robust transmitted waveform based on SINR criterion and MI criterion, the influence on the variation trend of SINR and MI is explored, and the range of critical value of Ty is found. The longer the echo observation time is, the better the performance of the SINR-based transmitted waveform over the MI-based transmitted waveform is. For the mutual information between the target and the echo, the performance of the MMA algorithm is better than the improved water-filling algorithm.

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“…Let ε 0 � 1, so with total energy X max � 5, you can distribute 0, 1, 2, 3, 4, or 5 units of energy to x(1), x (2), x (3), or x (4).…”

Section: Maximum Marginal Allocationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Robust Waveform Design Based on Bisection and Maximum Marginal Allocation Methods with the Concept of Information Entropy

Wang

Hao

2020

Mathematical Problems in Engineering

Self Cite

View full text Add to dashboard Cite

show abstract

“…The research shows that, for any target, the robust waveform will limit the performance in the worst case. In [9], the authors present a robust waveform design method based on mutual information. This method can alleviate the situation that the prior information of radar target cannot meet the parameter estimation, and further guarantee the performance of parameter estimation.…”

Section: Introductionmentioning

confidence: 99%

“…In [1,3,4], the authors focus on the signal to interference plus noise ratio when they study the optimization of radar waveform. In [2,6,7,[9][10][11]13], the authors study on the basis of the relevant knowledge of information theory. They focus on maximizing or minimizing mutual information and relative entropy as the criterion of radar waveform optimization.…”

Section: Introductionmentioning

confidence: 99%

“…They focus on maximizing or minimizing mutual information and relative entropy as the criterion of radar waveform optimization. The waveforms designed in [1,4,8,9] are all minmax robust waveforms, and in [3,8,12], the optimization criteria are all power. In [7], the authors mainly study spectral variance and information theory, and also mention the concept of correlation measure range.…”

Section: Introductionmentioning

confidence: 99%

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Multi-Target Robust Waveform Design Based on Harmonic Variance and Mutual Information

Wang

2020

Advances in Mathematical Physics

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Cognitive radar is an intelligent radar system, and adaptive waveform design is one of the core problems in cognitive radar research. In the previous studies, it is assumed that the prior information of the target is known, and the definition of target spectrum variance has not changed. In this paper, we study on robust waveform design problem in multiple targets scene. We hope that the upper and lower bounds of the uncertainty range of robustness are more close to the actual situation, and establish a finite time random target signal model based on mutual information (MI). On the basis of the optimal transmitted waveform and robust waveform based on MI, we redefine the target spectrum variance as harmonic variance, and propose a novel robust waveform design method based on harmonic variance and MI. We compare its performance with robust waveform based on original variance. Simulation results show that, in the situation of multiple targets, compared to the original variance, the MI lifting rate of robust waveform based on harmonic variance relative to the optimal transmitted waveform in the uncertainty range has great improvement. In certain circumstances, robust waveform based on harmonic variance and MI is more suitable for more targets.

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Robust Waveform Design Based on Jammer Games in Cognitive Radar

Cited by 2 publications

References 8 publications

Robust Waveform Design Based on Bisection and Maximum Marginal Allocation Methods with the Concept of Information Entropy

Robust Waveform Design Based on Bisection and Maximum Marginal Allocation Methods with the Concept of Information Entropy

Multi-Target Robust Waveform Design Based on Harmonic Variance and Mutual Information

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