科研成果详情

This paper studies the problem of real-time wireless localization for mobile group users, which can be used in many applications such as fire rescue and safety management in construction sites. However, due to the mobility of users and the instability of wireless signals, we find that traditional localization methods do not perform well, and the localization accuracy is thus not acceptable. To solve this problem, we propose to localize mobile users by exploiting their interrelated information. The mutual distance information among the users are exploited to get better localization performance for all the users. We first theoretically prove that the proposed scheme can improve the localization probability and accuracy. Furthermore, an Interoperable Localization Method (ILM) is designed, which extends the Kalman filter to alleviate the influence of noisy and unstable wireless signals. Finally, extensive experimental results demonstrate that our method outperforms the fixed anchor-based methods by 20%–45% in terms of localization accuracy and 20%–50% in terms of localization probability.