Novel Electromagnetic-Based Radar Propagation Model for Vehicular Sensing

被引:0
|
作者
Moulin, Francois De Saint [1 ]
Al Khalifeh, Khaldoun [1 ]
Craeye, Christophe [1 ]
Vandendorpe, Luc [1 ]
Oestges, Claude [1 ]
机构
[1] UCLouvain, ICTEAM, B-1348 Louvain La Neuve, Belgium
来源
IEEE ACCESS | 2024年 / 12卷
关键词
Radar; Mathematical models; Radar cross-sections; Computational modeling; Geometry; Analytical models; Stochastic processes; Electromagnetism; propagation; path-loss; radar; vehicular; radar cross-section; stochastic geometry; AUTOMOTIVE RADAR; STOCHASTIC GEOMETRY; PHYSICAL OPTICS; INTERFERENCE; RCS; OPTIMIZATION; PROBABILITY;
D O I
10.1109/ACCESS.2024.3456431
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
With the increased carrier frequencies envisioned for future radar and communication systems, transmissions in the near-field propagation region have raised an increased interest. In order to evaluate the performance of such systems, accurate propagation models are required to predict efficiently the received powers at each node, and draw correct conclusions. In this paper, we develop new radar propagation models based on ElectroMagnetic (EM) theory, helping to clarify in which cases popular models from the literature, namely the radar equation and the Geometrical Optics (GO) approximation, are valid. The target is modelled as a flat square or curved rectangular plate, enabling to compute analytically the scattered EM fields, and evaluate accurate Radar Cross-Sections (RCS). With a flat plate, the novel model directly highlights the link between the radar equation and the GO approximation, used e.g. in ray-tracing applications. Radar cross-section measurements are then performed in order to validate the models with multiple target geometries, e.g. square plates, sphere and cylinder. Finally, the impact of such modelling is evaluated by considering popular automotive scenarios, within the stochastic geometry framework.
引用
收藏
页码:128201 / 128214
页数:14
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