Abstract
To solve problems of low positioning accuracy and long time-consuming in indoor visible light three-dimensional positioning system, a visible light three-dimensional positioning method based on the improved hybrid bat algorithm (IHBA) is proposed in this paper. Firstly, some beacon points are set at the beginning of the IHBA to reduce the number of iterations. Secondly, weight coefficient is defined to improve positioning accuracy when the fitness function is constructed. Thirdly, aiming at controlling the search speed reasonably, an adaptive search factor is introduced while the bat individual update formula is designed. Finally, the chaotic perturbation operation is used to avoid the algorithm falling into local optimum. In indoor simulation environment, the size of which is 5m × 5m × 3m, the average positioning error of the IHBA is 1.16 cm and the positioning time is 1.85s. To verify the actual effectiveness of IHBA, a receiver is placed in the experimental environment, the size of which is 1.5m × 1.2m × 2m. Through the optical power detected by the receiver, the processor calculate its coordinates with IHBA. The average positioning error of the IHBA is 3.64 cm and the positioning time is 0.89 s. The proposed algorithm has practical application value in existing indoor positioning methods.
Highlights
In recent years, location-based services have become a significant part of our daily lives
To solve the above problem, we propose an improved hybrid bat algorithm (IHBA)
Point A is at the center, point B is at the edge, and point C is at the corner as the points to be located, which is used to test the positioning error of IHBA, and the coordinates of them are (2.5.2.5,1), (2.5,0.5,1), (4,4,1) separately
Summary
Location-based services have become a significant part of our daily lives. Visible light communication (VLC) positioning system is becoming a research hot owing to its low cost, low delay, high precision and anti-electromagnetic interference [9]–[12]. Numerous visible light three-dimensional (3-D) positioning algorithms have been proposed, some of them are still limited in application. In [24], the visible light positioning method based on improved genetic algorithm was proposed, which resulted in a large positioning delay. In reference [25], Wang proposed an indoor VLC three-dimensional positioning system based on immune algorithm. In [26], the visible light positioning method based on bat algorithm was proposed, which achieved the rapid positioning. In [27], the authors built a three-dimensional visible light positioning method based on chaotic particle swarm optimization.
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