Real-time VLP demonstrates over 97% decoding success in indoor environments, indicating significant advancements in smartphone sensor integration.
Visible Light Positioning (VLP), leveraging Light-Emitting Diodes (LEDs) and smartphone CMOS cameras, provides a high-precision solution for indoor localization. However, existing systems face challenges in accuracy, latency, and robustness due to line-of-sight (LOS) limitations and inefficient signal encoding. To overcome these constraints, this paper introduces a real-time VLP framework that integrates Multi-Pulse Position Modulation (MPPM) with smartphone multi-sensor fusion. By employing MPPM, a high-efficiency encoding scheme, the proposed system transmits LED identifiers (LED-IDs) with reduced inter-symbol interference, enabling robust signal detection even under dynamic lighting conditions and at extended distances. The smartphone’s camera is a receiver that decodes the MPPM-encoded LED-ID, while accelerometer and magnetometer data compensate for device orientation and motion-induced errors. Experimental results demonstrate that the MPPM-driven approach achieves a decoding success rate of over 97% at distances up to 2.4 m, while maintaining a frame processing rate of 30 FPS and sub-35 ms latency. Furthermore, the method reduces angular errors through sensor fusion, yielding 2D positioning accuracy below 10 cm and vertical errors under 16 cm across diverse smartphone orientations. The synergy of MPPM’s spectral efficiency and multi-sensor correction establishes a new benchmark for VLP systems, enabling scalable deployment in real-world environments without requiring complex infrastructure.
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Nguyen et al. (2025) studied this question.
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