# Leveraging Hybrid RF-VLP for High-Accuracy Indoor Localization with Sparse Anchors
###### Abstract  
Indoor low-power positioning systems have received much attention, and visible light positioning (VLP) shows great potential for its high accuracy and low power consumption. However, VLP also exhibits some limitations like small coverage area and the requirement of line of sight. Moreover, most VLP applications require the receiver to be within the coverage of at least three LEDs simultaneously, which seriously confines the availability of VLP when LEDs are sparsely deployed. Conversely, radio frequency (RF)-based positioning systems provide large coverage area, but suffer from low positioning accuracy due to multipath interference. In this work, we harnessed the complementary strengths of multiple technologies to develop a hybrid RF-VLP indoor positioning system for improving localization accuracy under sparse anchors. The RF-network-assisted visible light positioning enables each receiver to determine its position autonomously, using signals from a single LED anchor and neighboring receivers, and without needing RF anchors. To validate the effectiveness of the proposed method, we utilize commercial off-the-shelf LED and ESP32 to build up a prototype system. Comprehensive experiments are performed to evaluate the performance of the positioning system, and the results show that the proposed system achieves an overall root mean square error (RMSE) of 26.1 cm, representing a 28.5% improvement in positioning accuracy compared to traditional RF-based positioning methods, which makes it highly feasible for deployment. visible light positioning (VLP); radio frequency positioning (RF-positioning); hybrid positioning; wireless sensor network (WSN) 202520202520252025202025202025  
such as retail and logistics. However, it also has limitations, including multipath interference and reduced accuracy in dynamic environments [9]. High infrastructure requirements and periodic maintenance for battery-powered beacons add to operational costs, while security vulnerabilities can impact data integrity. VLP on the other hand, offers high precision and immunity to radio-frequency interference, making it particularly effective in indoor environments where other signals may falter [10]. Since it uses existing LED lighting, VLP can easily integrate with the infrastructure, often reducing the installation costs and energy consumption, making it a promising option for indoor positioning applications [11; 12; 13; 14; 15; 16]. However, VLP has limitations, including dependence on line-of-sight, which can disrupt signals in crowded spaces or if objects block the light source [17]. Furthermore, most VLP systems require the receiver to simultaneously acquire modulated optical signals from at least three LED anchors to achieve successful positioning [18; 19; 20], which seriously confines the availability of VLP when LEDs are sparsely deployed. Although some articles propose a single-LED anchor-based positioning system, a complex receiver design is required to achieve positioning [21; 22], which increases the cost and complexity of the system. Focusing on applications such as factory automation, conveyors and robots usually need to perform localization under dynamic conditions. This process demands high levels of continuity, real-time responsiveness, and extensive coverage for target localization, rendering single localization methods insufficient to meet these complex requirements. Since the RF and VLP systems are somewhat complementary to each other, the concept of a hybrid RF-VLP has become a new research trend. [PERSON] et al. [23] proposed a BLE-VLC hybrid indoor positioning network, where BLE trilateration is fused with VLP distance information to obtain better positioning results. In [24], [PERSON] et al. used the intensities of different wavelengths of light from various LED beacons and the signal strengths from different Bluetooth beacons to train a deep neural network (DNN). The trained model is then used to locate the target. [PERSON] et al.