Abstract
Indoor navigation applications have become widespread in recent years with the ability of mobile phones which determine the position. Due to the inefficiency of global positioning system (GPS) indoors, other positioning methods have been developed based on local networks using technologies such as Bluetooth, wireless networks, ultra-wideband signals, ultrasonic signals, and radio frequency identification modules. Various technologies yield high or medium accuracy. Combining data from multiple sources via fusion enhances location precision. In this study, indoor positions were estimated using trilateration with Bluetooth devices, and the accuracy was improved by applying filters to the data from inertial measurement unit (IMU) sensors on the phone. As a result of combining Bluetooth and IMU data with data fusion, submeter accuracy was achieved. The results obtained were tested at Yildiz Technical University-Istanbul Türkiye. It was determined that 92% of the data was obtained with submeter accuracy.
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