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Guangkun Zhang

Publications and source records attributed to Guangkun Zhang.

2 recordsLinked to original sources

High-Resolution Multi-Target DOA Estimation for Resonant Beam Systems

Direction of arrival (DOA) estimation technology offers a promising solution to address the sensing and positioning demands of Internet of Things (IoT) devices. Optical resonant beam systems (RBS), owing to their inherent characteristics of self-alignment, self-established energy focusing, and passive target sensing, make them naturally suited for {\color{blue}DOA} estimation in IoT scenarios. However, RBS suffer from limited angular resolution and a narrow field of view (FoV) in multi-target environments. To overcome these limitations, this paper proposes a high-resolution wide-field-of-view resonant beam DOA estimation system (RB-HWDOA). The RB-HWDOA integrates an optical spectrum-based DOA estimation algorithm (OSB-DOA), which leverages amplitude information in the two-dimensional Fourier spectrum of the resonant beam, {\color{blue}overcoming the resolution limit imposed by the beam size in spatial-domain methods}. Furthermore, we designed a {\color{blue}telescope} modulation (TM) structure to correct phase and direction mismatches, enabling a multi-Tx framework that focuses beams onto a common sensing module, thereby extending the effective FoV. Combined with the OSB-DOA algorithm, this design supports high-resolution DOA estimation for {\color{blue}multiple targets simultaneously over a wide FoV}. Simulation results show that OSB-DOA resolves angular separations down to $0.1^{\circ}$ across multiple resonant beams, remains robust under noise, {\color{blue}and the TM architecture enables multi-Tx integration for wide-FoV coverage}, making RB-HWDOA a scalable and efficient solution for passive multi-target DOA estimation in complex IoT environments.

physics.optics

Simultaneous Self-Localization and Base Station Localization with Resonant Beam

High-precision positioning in GPS-denied environments is a demanding but challenging technology. Resonant Beam Positioning (RBP) utilizes a resonant beam with properties such as energy focusing, self-establishment, self-alignment, and passive operation, offering a promising solution for this task. However, traditional RBP algorithms require a fixed number of resonant beam base stations, which can be costly to expand coverage. To address this limitation, we propose a distributed resonant beam positioning (DRBP) system that simultaneously estimates the base station and mobile target (MT) positions. Firstly, the MT receives resonant beam samples to locate the base station in the limited field of view (FoV) region. Subsequently, it estimates self-position based on the known locations of the base stations. During moving, the DRBP system facilitates self-positioning on the MT side, enabling dynamic expansion of both the number of base stations and the coverage area. Numerical results demonstrate that DRBP achieves a positioning root mean square error (RMSE) of $0.1$ m and a rotation RMSE of 2$^\circ$, validating the system's high accuracy.

physics.optics