Acta Optica Sinica, Volume. 45, Issue 12, 1226001(2025)
Radar Filtering Detection Utilizing Coaxial Vortex Modulations via Spiral Multi-Pinhole Array
Radar systems, which acquire precise target information through electromagnetic wave transmission and reception, maintain critical strategic importance in both national defense security and civil monitoring applications. To address the persistent challenge of limited detection accuracy in conventional radar systems under complex electromagnetic environments, this study introduces a novel radar detection system incorporating vortex beams with distinct topological properties, establishing a spiral multi-pinhole array coaxial vortex modulated radar filtering detection scheme. Utilizing the unique spatial characteristics of the vortex signal beam and stray light components, this radar detection system enables target information acquisition without noise interference, thereby substantially enhancing detection accuracy.
The proposed coaxial vortex radar system employs a dual-stage phase modulation process with a spiral multi-pinhole array, encompassing vortex detection beam generation through phase modulation and vortex signal beam reconstruction via conjugate phase matching. Based on the differential modulation effects for the vortex signal beam and stray light, effective noise-suppressed radar filtering detection is achieved by utilizing the spatial separation characteristics arising from topological differences. Through integrated theoretical analyses and numerical simulations, we systematically examine the generation of vortex detection beam, reconstruction of the vortex signal beam, and spatially filtering detection of noise-suppression. The theoretical framework applies diffraction optics principles to analyze coaxial vortex modulation mechanics. The numerical simulations utilizing wave propagation algorithms illuminate spatial evolution characteristics, including intensity distributions, phase profiles, and signal-noise spatially separational filtrations.
The results present a comprehensive analysis of the coaxial vortex modulations in radar detections. The theoretical modeling confirms that the coaxial modulations through the spiral multi-pinhole array generate the vortex signal beam exhibiting the central brightness intensity distribution with topological charge of l+l′=0. In contrast to stray light, the natural noise beam displays the vortex characteristics of an annular intensity with topological charge of l′. These findings theoretically demonstrate the fundamental differences in topological characteristics between the vortex signal beam and natural vortex beam. Combined with numerical simulations, the parametric analyses reveal increasing spatial separation efficiency with higher topological orders [Fig. 4(a)]. Consequently, to achieve complete noise-suppression, the topological charge must exceed a critical order, specifically at least 4-order in our configuration [Figs. 4(b)?4(d)].
This study presents a novel radar detection system based on the coaxial modulations of vortex beams by a spiral multi-pinhole array. The dual-stage vortex modulation system creates inherent topological differences between vortex signal and stray components, resulting in distinct spatial distributions. Utilizing the spatially separational filtrations, this radar detection system effectively filters out stray interference and achieves complete noise-suppression. This research not only validates the feasibility of vortex modulations in radar detection but also establishes a paradigm for deep fusion of photon orbital angular momentum and classical radar technology, providing crucial technical support for photoelectric fusion detection technology systems.
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Li Ma, Ying Wang, Ying Zhang, Min Li, Xiangyu Wang, Pengcheng Liu, Yaru Gao. Radar Filtering Detection Utilizing Coaxial Vortex Modulations via Spiral Multi-Pinhole Array[J]. Acta Optica Sinica, 2025, 45(12): 1226001
Category: Physical Optics
Received: Feb. 10, 2025
Accepted: Apr. 24, 2025
Published Online: Jun. 23, 2025
The Author Email: Yaru Gao (gaoyaru@sdnu.edu.cn)
CSTR:32393.14.AOS250581