Research on Jamming Method of False Target Based on Micro-Motion Modulation

2014 ◽  
Vol 556-562 ◽  
pp. 2707-2710
Author(s):  
Rui Cui ◽  
Ai Guo Sheng ◽  
Ji Fei Pan ◽  
Bing He ◽  
Jing Zhu
Keyword(s):  
Unique Feature ◽  
Target Recognition ◽  
Doppler Imaging ◽  
Radar Target ◽  
Target Image ◽  
Imaging Model ◽  
False Target ◽  
Micro Motion ◽  
Rotating Target

Micro-Doppler is a unique feature of radar target, and has been applied to target recognition of ISAR widely, but it can also destroy the quality of the target image at the same time. So a novel jamming method of false target base on Micro-Doppler modulation is presented in the paper. The phase of captured radar transmitting signal is been modulated, which can generate false Micro-Doppler features. The micro-Doppler imaging model of the rotating target is analyzed, and the jamming model based on Micro-Motion modulation is given. Finally, the simulation of jamming experiment is carried out. The results of simulation prove the method is corrective and effective.

Radar target recognition based on few-shot learning

2021 ◽  
Author(s):  
Yue Yang ◽  
Zhuo Zhang ◽  
Wei Mao ◽  
Yang Li ◽  
Chengang Lv
Keyword(s):  
Target Recognition ◽  
Radar Target ◽  
Radar Target Recognition

scholarly journals Improving Web QoE Monitoring for Encrypted Network Traffic through Time Series Modeling

2021 ◽  
Vol 48 (4) ◽  
pp. 37-40
Author(s):  
Nikolas Wehner ◽  
Michael Seufert ◽  
Joshua Schuler ◽  
Sarah Wassermann ◽  
Pedro Casas ◽  
...  
Keyword(s):  
Neural Networks ◽  
Time Series ◽  
Recurrent Neural Networks ◽  
Quality Of Experience ◽  
Unique Feature ◽  
Time Series Modeling ◽  
Web Browsing ◽  
Large Dataset ◽  
Efficient Approximation

This paper addresses the problem of Quality of Experience (QoE) monitoring for web browsing. In particular, the inference of common Web QoE metrics such as Speed Index (SI) is investigated. Based on a large dataset collected with open web-measurement platforms on different device-types, a unique feature set is designed and used to estimate the RUMSI - an efficient approximation to SI, with machinelearning based regression and classification approaches. Results indicate that it is possible to estimate the RUMSI accurately, and that in particular, recurrent neural networks are highly suitable for the task, as they capture the network dynamics more precisely.

scholarly journals Modeling and image quality enhancement for dynamic compressive imaging system

2021 ◽  
Vol 15 ◽  
pp. 174830262110080
Author(s):  
Changjun Zha* ◽  
Qian Zhang* ◽  
Huimin Duan
Keyword(s):  
Image Quality ◽  
Imaging System ◽  
Quality Enhancement ◽  
Target Image ◽  
Compressive Imaging ◽  
Image Quality Enhancement ◽  
System A ◽  
Single Column ◽  
The Impact

Traditional single-pixel imaging systems are aimed mainly at relatively static or slowly changing targets. When there is relative motion between the imaging system and the target, sizable deviations between the measurement values and the real values can occur and result in poor image quality of the reconstructed target. To solve this problem, a novel dynamic compressive imaging system is proposed. In this system, a single-column digital micro-mirror device is used to modulate the target image, and the compressive measurement values are obtained for each column of the image. Based on analysis of the measurement values, a new recovery model of dynamic compressive imaging is given. Differing from traditional reconstruction results, the measurement values of any column of vectors in the target image can be used to reconstruct the vectors of two adjacent columns at the same time. Contingent upon characteristics of the results, a method of image quality enhancement based on an overlapping average algorithm is proposed. Simulation experiments and analysis show that the proposed dynamic compressive imaging can effectively reconstruct the target image; and that when the moving speed of the system changes within a certain range, the system reconstructs a better original image. The system overcomes the impact of dynamically changing speeds, and affords significantly better performance than traditional compressive imaging.

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