The Aggregated Electromagnetic Vortex Wave and Multi-Modal Imaging Experiment

Electromagnetic vortex waves have received widespread attention in many fields due to their unique physical characteristics. The information dimension provided by vortex electromagnetic waves brings possibilities for future breakthroughs in radar detection and imaging. This article proposes a multi-modal aggregated electromagnetic vortex wave generation method for the first time. Moreover, it conducts vehicle imaging experiments to verify the method's practicality. The core element of the experiment is to simultaneously generate multiple-mode electromagnetic vortex wave signals with energy accumulation and perform fusion processing. Firstly, multiple orbital angular momentum (OAM) modes are superimposed to generate a mode group, and the initial phase of the modes in the mode group is further controlled to synthesize aggregated electromagnetic vortex waves. Based on the generation of aggregated vortex waves, imaging experiments were conducted using a vehicle-mounted setup. The experimental procedure and multi-modal fusion results were presented. It has been shown that the energy of the main lobe signal of the image target is enhanced by utilizing multi-modal vortex radar information fusion, which can improve the signal-to-noise ratio of the target imaging.

Authors

Institutions

Publication Details

Journal
Sensors
Published
2025-10-25
DOI
https://doi.org/10.3390/s25216578
Primary Topic
Orbital Angular Momentum in Optics
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The Aggregated Electromagnetic Vortex Wave and Multi-Modal Imaging Experiment

Kang Liu, Caipin Li, Dong Gil You, Shengyuan Li et al.
Sensors
Orbital Angular Momentum in Optics
article

The Aggregated Electromagnetic Vortex Wave and Multi-Modal Imaging Experiment

Kang Liu, Caipin Li, Dong Gil You, Shengyuan Li, Xiaomin Tan, Jiao Liu, Shitao Zhu, Zhuo Zhang, Yifeng He, Wencan Peng, Tao Wu
article en

Abstract

Electromagnetic vortex waves have received widespread attention in many fields due to their unique physical characteristics. The information dimension provided by vortex electromagnetic waves brings possibilities for future breakthroughs in radar detection and imaging. This article proposes a multi-modal aggregated electromagnetic vortex wave generation method for the first time. Moreover, it conducts vehicle imaging experiments to verify the method's practicality. The core element of the experiment is to simultaneously generate multiple-mode electromagnetic vortex wave signals with energy accumulation and perform fusion processing. Firstly, multiple orbital angular momentum (OAM) modes are superimposed to generate a mode group, and the initial phase of the modes in the mode group is further controlled to synthesize aggregated electromagnetic vortex waves. Based on the generation of aggregated vortex waves, imaging experiments were conducted using a vehicle-mounted setup. The experimental procedure and multi-modal fusion results were presented. It has been shown that the energy of the main lobe signal of the image target is enhanced by utilizing multi-modal vortex radar information fusion, which can improve the signal-to-noise ratio of the target imaging.

SensorsVol. 25(21)
National University of Defense Technology (CN), China Academy of Space Technology (CN), Aerospace Information Research Institute (CN), Xi'an Jiaotong University (CN)
National Key Research and Development Program of China
Openalex Percentile: Top 75%
Orbital Angular Momentum in Optics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.