scholarly journals Adaptive Waveform Design for Cognitive Radar in Multiple Targets Situation

Entropy ◽  
2018 ◽  
Vol 20 (2) ◽  
pp. 114 ◽  
Author(s):  
Xiaowen Zhang ◽  
Xingzhao Liu
Keyword(s):  
Waveform Design ◽  
Cognitive Radar ◽  
Multiple Targets

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

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Bin Wang ◽  
Shuangqi Yu
Keyword(s):  
Mutual Information ◽  
Design Method ◽  
Waveform Design ◽  
Upper And Lower Bounds ◽  
Cognitive Radar ◽  
Multiple Targets ◽  
Uncertainty Range ◽  
Target Spectrum ◽  
Definition Of ◽  
Transmitted Waveform

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.

scholarly journals COGNITIVE RADAR WAVEFORM DESIGN AGAINST SIGNAL-DEPENDENT MODULATED JAMMING

2018 ◽  
Vol 80 ◽  
pp. 59-77 ◽  
Author(s):  
Shuping Lu ◽  
Guolong Cui ◽  
Xianxiang Yu ◽  
Lingjiang Kong ◽  
Xiaobo Yang
Keyword(s):  
Waveform Design ◽  
Cognitive Radar

MIMO Radar Waveform Design in the Presence of Multiple Targets and Practical Constraints

2020 ◽  
Vol 68 ◽  
pp. 1974-1989 ◽  
Author(s):  
Xianxiang Yu ◽  
Khaled Alhujaili ◽  
Guolong Cui ◽  
Vishal Monga
Keyword(s):  
Waveform Design ◽  
Mimo Radar ◽  
Multiple Targets ◽  
Practical Constraints

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

2020 ◽  
Vol 2020 ◽  
pp. 1-23
Author(s):  
Bin Wang ◽  
Xiaolei Hao
Keyword(s):  
Mutual Information ◽  
Optimization Design ◽  
Waveform Design ◽  
Observation Time ◽  
Cognitive Radar ◽  
Bisection Algorithm ◽  
Water Filling ◽  
Water Filling Algorithm ◽  
Concept Of Information ◽  
Transmitted Waveform

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.

Cognitive radar waveform design for spectral coexistence

2013 ◽  
Author(s):  
Marco Piezzo ◽  
Antonio De Maio ◽  
Augusto Aubry ◽  
Alfonso Farina
Keyword(s):  
Waveform Design ◽  
Cognitive Radar
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