多观测值约束的可见光定位算法

doi:10.3969/j.issn.1001-2400.2017.04.027

Abstract

Abstract:

In the indoor visible light transmission environment with complex noise, traditional received signal strength indication(RSSI)localization algorithm and imaging localization algorithm are unable to accurately determine the reason of the inaccurate localization model and inadequate constraints of position coordinates. In order to solve the problems, a visible light localization algorithm based on multi-measurements constraints is presented in the paper. The algorithm first constructs a joint localization state space model based on RSSI localization and the imaging localization algorithm. Then, states, measurements and their equations are constructed based on the space model. Finally, the equations are resolved using the unscented Kalman filter(UKF). Compared with RSSI localization and imaging localization, simulation results show that the RMSE of the proposed algorithm could be closer to the Cramer Rao bound. Besides, the localization probability of the proposed algorithm is higher than that of RSSI localization and imaging localization algorithm.

Key words: visible light, indoor positioning system, image sensor, Cramer-Rao lower bounds

LU Hang;CUI Weijia;BA Bin;LU Zhiyu. Visible light localization algorithm based on multi-measurements constraints[J].Journal of Xidian University, 2017, 44(4): 156-161.

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[1]	XIE Fan,FENG Lifang. Visible light assisted relay communication system and a power allocation scheme [J]. Journal of Xidian University, 2020, 47(1): 95-103.
[2]	ZHAO Xiang;LIN Jiming. Theoretical limit of the indoor visible light-image sensor positioning system [J]. Journal of Xidian University, 2016, 43(4): 63-68.

Visible light localization algorithm based on multi-measurements constraints

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