Resonant Beam Enabled Multi-Target Localization
Guangkun Zhang, Mengyuan Xu, Yunfeng Bai, Fang Wen, Mingliang Xiong, Mingqing Liu, Siyuan Du, Gang Li, Bin He, Qingwen Liu
- 发表年份
- 2025
- 引用次数
- 2
摘要
In the era of the Internet of everything (IoE) and the metaverse, there is a growing demand for high-accuracy indoor positioning for applications such as autonomous robots, virtual reality, and smartphones. This paper proposed a resonant beam phase-based passive localization (RBPPL) system optimized for high-precision indoor positioning in multi-access scenarios. By leveraging the self-alignment characteristic and integrating the analysis of resonant beam phase, angle of arrival (AoA) matching and binocular disparity method for 3D point coordinate acquisition, the RBPPL system achieves binocular passive multi-access 3D positioning with an error within 4 cm at a distance of 8 m. We present a novel multi-access AoA estimation method that overcomes the challenges of spot overlap in traditional CMOS-based angle analysis. We propose a telescope system to correct the phase and focus the propagation direction of optical resonant beam systems. Simulations demonstrate the system’s robustness and high accuracy. The proposed RBPPL system, optimized for multi-access scenarios, offers a promising solution for high-accuracy indoor positioning, supporting various IoE and metaverse applications. Future work will focus on real-world deployment and its potential in complex multi-access scenarios.
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