Computer Engineering and Applications ›› 2019, Vol. 55 ›› Issue (9): 65-71.DOI: 10.3778/j.issn.1002-8331.1801-0416

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Indoor Self-Adaption Positioning Algorithm Based on Improved Particle Filter

HU Donghai, SHAO Yuan, CHEN Ying, XIA Shixiong   

  1. School of Computer Science and Technology, China University of Mining and?Technology, Xuzhou, Jiangsu 221116, China
  • Online:2019-05-01 Published:2019-04-28


胡东海,邵  元,陈  莹,夏士雄   

  1. 中国矿业大学 计算机科学与技术学院,江苏 徐州 221116

Abstract: Accurate indoor positioning system has important research and application value. There are many constraints when GPS is used in indoor positioning so that it cannot provide accurate indoor positioning service, so how to improve the accuracy of indoor positioning system has become the focus of current research. In order to reduce the indoor environment impact and improve the positioning accuracy, an indoor positioning algorithm based on improved particle filter is proposed in this paper. The main idea of the algorithm is to receive transmitted signal from the AP by mobile devices, like mobile phones, and then to set up a signal attenuation model according to indoor topology. The signal attenuation model is used to assist particle filtering to locate the mobile devices. In the positioning process, mobile devices use self-adaption signal acquisition methods to receive signals, and the idea of random walk and the method of auto-optimal re-sampling are introduced to improved particle filter. Simulation results show that this algorithm can effectively improve the accuracy and robustness of indoor positioning.

Key words: indoor positioning, signal attenuation model, self-adaption method, improve particle filter

摘要: 精确的室内定位系统具有重要的研究及应用价值。由于GPS在室内受到很多约束条件而无法提供精确的室内定位服务,如何提高室内定位算法的精度已经成为当前研究的热点。通过提出一种基于改进粒子滤波的室内定位算法以减少室内环境影响来提高定位精度。该算法主要思想是通过手机等移动设备接收AP传播的信号,然后根据室内拓扑建立一个信号衰减模型,在移动设备的移动过程中结合粒子滤波进行定位。在定位过程中,移动设备采用自适应的信号采集方法来接收信号,同时随机游走思想和自优化的重采样方法被用来改进粒子滤波。仿真实验结果表明该算法能够有效提高室内定位的精度和鲁棒性。

关键词: 室内定位, 信号衰减模型, 自适应算法, 改进粒子滤波