Brida Peter, Machaj Juraj, Racko Jan, Krejcar Ondrej
Department of Multimedia and Information Communication Technology, Faculty of Electrical Engineering and Information, University of Zilina, Univerzitna 1, 01026 Zilina, Slovakia.
Center for Basic and Applied Research, Faculty of Informatics and Management, University of Hradec Kralove, Rokitanskeho 62, 500 03 Hradec Kralove, Czech Republic.
Sensors (Basel). 2021 Mar 24;21(7):2283. doi: 10.3390/s21072283.
While a vast number of location-based services appeared lately, indoor positioning solutions are developed to provide reliable position information in environments where traditionally used satellite-based positioning systems cannot provide access to accurate position estimates. Indoor positioning systems can be based on many technologies; however, radio networks and more precisely Wi-Fi networks seem to attract the attention of a majority of the research teams. The most widely used localization approach used in Wi-Fi-based systems is based on fingerprinting framework. Fingerprinting algorithms, however, require a radio map for position estimation. This paper will describe a solution for dynamic radio map creation, which is aimed to reduce the time required to build a radio map. The proposed solution is using measurements from IMUs (Inertial Measurement Units), which are processed with a particle filter dead reckoning algorithm. Reference points (RPs) generated by the implemented dead reckoning algorithm are then processed by the proposed reference point merging algorithm, in order to optimize the radio map size and merge similar RPs. The proposed solution was tested in a real-world environment and evaluated by the implementation of deterministic fingerprinting positioning algorithms, and the achieved results were compared with results achieved with a static radio map. The achieved results presented in the paper show that positioning algorithms achieved similar accuracy even with a dynamic map with a low density of reference points.
尽管最近出现了大量基于位置的服务，但室内定位解决方案仍在不断发展，以便在传统的基于卫星的定位系统无法提供准确位置估计的环境中提供可靠的位置信息。室内定位系统可以基于多种技术；然而，无线网络，更确切地说是Wi-Fi网络，似乎吸引了大多数研究团队的关注。基于Wi-Fi的系统中最广泛使用的定位方法是基于指纹识别框架。然而，指纹识别算法需要一个无线电地图来进行位置估计。本文将描述一种动态无线电地图创建的解决方案，旨在减少构建无线电地图所需的时间。所提出的解决方案使用来自惯性测量单元（IMU）的测量数据，并通过粒子滤波航位推算算法进行处理。然后，由实现的航位推算算法生成的参考点（RP）通过所提出的参考点合并算法进行处理，以优化无线电地图的大小并合并相似的参考点。所提出的解决方案在实际环境中进行了测试，并通过确定性指纹识别定位算法的实现进行了评估，同时将所取得的结果与使用静态无线电地图所取得的结果进行了比较。本文给出的结果表明，即使使用参考点密度较低的动态地图，定位算法也能达到相似的精度。
