Reconfigurable and single-shot chirped microwave pulse compression using a time-spectrum convolution system

Author(s):  
Ming Li ◽  
Antonio Malacarne ◽  
Sophie LaRochelle ◽  
Jianping Yao ◽  
Jose Azana
2012 ◽  
Vol 365 ◽  
pp. 012056 ◽  
Author(s):  
Vasudha Rajput ◽  
N Parmar ◽  
K S Bhat ◽  
K P Maheswari ◽  
Y Choyal

2010 ◽  
Vol 22 (4) ◽  
pp. 849-852
Author(s):  
沈旭明 Shen Xuming ◽  
张鹏 Zhang Peng ◽  
和天慧 He Tianhui

1986 ◽  
Vol 57 (10) ◽  
pp. 2475-2480 ◽  
Author(s):  
R. A. Alvarez ◽  
D. P. Byrne ◽  
R. M. Johnson

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 4034 ◽  
Author(s):  
Junfei Yu ◽  
Jingwen Li ◽  
Bing Sun ◽  
Jie Chen ◽  
Chunsheng Li

Radio frequency interference (RFI) is known to jam synthetic aperture radar (SAR) measurements, severely degrading the SAR imaging quality. The suppression of RFI in SAR echo signals is usually an underdetermined blind source separation problem. In this paper, we propose a novel method for multiclass RFI detection and suppression based on the single shot multibox detector (SSD). First, an echo-interference dataset is established by randomly combining the target signal with various types of RFI in a simulation, and the time–frequency form of the dataset is obtained by utilizing the short-time Fourier transform (STFT). Next, the time–frequency dataset acts as input data to train the SSD and obtain a network that is capable of detecting, identifying and estimating the interference. Finally, all of the interference signals are exactly reconstructed based on the prediction results of the SSD and mitigated by an adaptive filter. The proposed method can effectively increase the signal-to-interference-noise ratio (SINR) of RFI-contaminated SAR echoes and improve the peak sidelobe ratio (PSLR) after pulse compression. The simulated experimental results validate the effectiveness of the proposed method.


1998 ◽  
Vol 43 (2) ◽  
pp. 209-215 ◽  
Author(s):  
S. N. Vlasov ◽  
N. G. Kazakova ◽  
E. V. Koposova

2012 ◽  
Vol 37 (8) ◽  
pp. 1355 ◽  
Author(s):  
Antonio Malacarne ◽  
Reza Ashrafi ◽  
Ming Li ◽  
Sophie LaRochelle ◽  
Jianping Yao ◽  
...  
Keyword(s):  

Sign in / Sign up

Export Citation Format

Share Document