scholarly journals Scattering and Doppler Spectral Analysis for a Fast-Moving Target above Time-Varying Lossy Dielectric Sea Surface

2016 ◽  
Vol 2016 ◽  
pp. 1-11
Author(s):  
Ke Li ◽  
Lixin Guo ◽  
Juan Li

A numerical electromagnetic method based on the physical optics with physical optics method (PO-PO) is employed to calculate backscattered returns from a missile-like target above sea surface. Surfaces are time-varying Monte Carlo simulations initialized as realizations of a Pierson–Moskowitz spectrum. The monostatic normalized radar cross section of composite model by the hybrid PO-PO method is calculated and compared with those by the conventional method of moments, as well as the runtime and memory requirements. The results are found to be in good agreement. The runtime shows that the hybrid PO-PO method enables large-scale time-varying Monte Carlo simulations. The numerical simulations of the Doppler spectrum from the fast-moving target above time-varying lossy dielectric sea surface are obtained, and the Doppler spectra of backscattered signals from this model are discussed for different incident angles, speed of flying target, wind speeds, incident frequencies, and target altitudes in detail. Finally, the coupling effects on Doppler spectra are analyzed. All the results are obtained at the incidence of horizontal polarization wave in this study.

2016 ◽  
Vol 30 (10) ◽  
pp. 1265-1276 ◽  
Author(s):  
Yunhua Wang ◽  
Yanmin Zhang ◽  
Huimin Li ◽  
Ge Chen

1998 ◽  
Vol 103 (C11) ◽  
pp. 24983-24989 ◽  
Author(s):  
Quanhua Liu ◽  
Clemens Simmer ◽  
Eberhard Ruprecht

Author(s):  
Jake L. Rafferty ◽  
Ling Zhang ◽  
Nikolaj D. Zhuravlev ◽  
Kelly E. Anderson ◽  
Becky L. Eggimann ◽  
...  

1996 ◽  
Vol 07 (03) ◽  
pp. 295-303 ◽  
Author(s):  
P. D. CODDINGTON

Large-scale Monte Carlo simulations require high-quality random number generators to ensure correct results. The contrapositive of this statement is also true — the quality of random number generators can be tested by using them in large-scale Monte Carlo simulations. We have tested many commonly-used random number generators with high precision Monte Carlo simulations of the 2-d Ising model using the Metropolis, Swendsen-Wang, and Wolff algorithms. This work is being extended to the testing of random number generators for parallel computers. The results of these tests are presented, along with recommendations for random number generators for high-performance computers, particularly for lattice Monte Carlo simulations.


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