Adaptive waveform design based on LSSVM for moving target recognition in cognitive radar

2012 ◽  
Author(s):  
Meimei Fan ◽  
Dongping Liao ◽  
Xiaofeng Ding ◽  
Xiang Li
Keyword(s):  
Target Recognition ◽  
Waveform Design ◽  
Moving Target ◽  
Cognitive Radar

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

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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