摘 要：传统基于指纹库构建的无线地图没有考虑室内环境中指纹会随着接收信号强度的变化而变化这一因素，所以系统鲁棒性较差。为了解决这一问题，提出了一种基于特征迁移的室内定位算法，采用最小化最大均值差异算法来减小离线与在线两个阶段所收集数据的分布差异。通过多次应用算法的实验研究，结果表明，在复杂多变的室内环境中定位准确率得到大幅提升，有效地克服了两个阶段指纹特征分布差异带来的影响。
关键词：室内定位；特征迁移；最大均值差异
DOI:10.19850/j.cnki.2096-4706.2021.02.012
中图分类号：TN92 文献标识码：A 文章编号：2096-4706（2021）02-0044-05
Research on Indoor Positioning Algorithm Based on Characteristics Migration
WAN Xiang
（School of Information Engineering，Guangdong University of Technology，Guangzhou 510006，China）
Abstract：The traditional wireless map constructed based on fingerprint database does not consider that fingerprint in the indoor environment will change with the change of the received signal strength，so the system has poor robustness. In order to solve this problem，an indoor positioning algorithm based on characteristics migration is proposed，using minimization the maximum mean discrepancy algorithm to reduce the distribution difference of the collected data between the offline and online stages. By means of several times of experimental study on application of algorithm，the experimental results show that the positioning accuracy in the complex indoor environments has greatly improved，and it effectively overcomes the influence of the distribution difference on fingerprint characteristics between the two stages.
Keywords：indoor positioning；characteristics migration；maximum mean discrepancy
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作者简介：万祥（1996—），男，汉族，湖南岳阳人，硕士在读，研究方向：室内定位。