Autor: |
Xiaochuan Deng, Cheng Liao, Dongmin Zhang, Ju Feng, Yuping Shang, Haijing Zhou |
Jazyk: |
angličtina |
Rok vydání: |
2020 |
Předmět: |
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Zdroj: |
IEEE Access, Vol 8, Pp 28450-28461 (2020) |
Druh dokumentu: |
article |
ISSN: |
2169-3536 |
DOI: |
10.1109/ACCESS.2020.2972365 |
Popis: |
The prediction of radar target echo signal in a large-scale complex environment is of great significance in target detection, radar design and other applications. In this paper, a novel PE/FDTD hybrid model is proposed to predict monostatic radar target echo signals in large-scale complex environments. The target echo signal can be regarded as the output response of the transmitted signal which passes through a linear time invariant system composed of complex environment and target. The transport function of the complex environment is computed by the parabolic equation (PE) method and the scattering characteristics of the target are calculated by finite difference time domain method (FDTD). The combination of PE and FDTD is realized through the system response function. In combination with the “stop-go” method, the prediction of moving target echo signal is realized. In addition, the error of combining PE with FDTD is analyzed, and the result shows that the error is less than 0.1% when the target distance is more than 10km. Additional numerical examples are given to demonstrate the correctness of the method in semi-space, rain, fog and atmospheric duct environments. The calculated results are compared with those of theoretical method, time-domain shooting and bouncing ray (TDSBR), multi-level fast multi-pole method (MLFMM) and waveguide mode theory, and good agreement among them is observed. Finally, the simulation analysis of the missile echo signal in the mixed sea-land environment with surface duct is carried out. The simulation results show that this model can be used to predict the echo signal of airborne targets in a large-scale complex environment. It is a promising option for multi-scale computing involving radar target and large-scale environment. |
Databáze: |
Directory of Open Access Journals |
Externí odkaz: |
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