BLE-Based Indoor Localization: Analysis of Some Solutions for Performance Improvement

BLE-Based Indoor Localization: Analysis of Some Solutions for Performance Improvement

8 January 2024 | Filippo Milano, Helbert da Rocha, Marco Laracca, Luigi Ferrigno, António Espírito Santo, José Salvado, Vincenzo Paciello
This paper investigates the performance improvement of indoor localization using a BLE-based system with anchor technology, focusing on the Received Signal Strength Indicator (RSSI) for distance estimation. The authors analyze various solutions proposed in the literature to enhance the performance of BLE-based indoor localization, including multichannel transmission, RSSI signal conditioning, and distance estimation techniques. An experimental campaign was conducted in a complex indoor environment to evaluate the effectiveness of these solutions. The results show that multichannel transmission, particularly with RSSI signal aggregation techniques, significantly improves localization accuracy, reducing the positioning error from 1.5 meters to about 1 meter. Other solutions, such as RSSI filtering and different distance estimation methods, had a lesser impact on performance, with positioning errors varying between a 2% decrease and a 23% increase. The study provides valuable insights for designers of indoor localization systems to choose the most effective solutions based on their specific performance requirements.This paper investigates the performance improvement of indoor localization using a BLE-based system with anchor technology, focusing on the Received Signal Strength Indicator (RSSI) for distance estimation. The authors analyze various solutions proposed in the literature to enhance the performance of BLE-based indoor localization, including multichannel transmission, RSSI signal conditioning, and distance estimation techniques. An experimental campaign was conducted in a complex indoor environment to evaluate the effectiveness of these solutions. The results show that multichannel transmission, particularly with RSSI signal aggregation techniques, significantly improves localization accuracy, reducing the positioning error from 1.5 meters to about 1 meter. Other solutions, such as RSSI filtering and different distance estimation methods, had a lesser impact on performance, with positioning errors varying between a 2% decrease and a 23% increase. The study provides valuable insights for designers of indoor localization systems to choose the most effective solutions based on their specific performance requirements.
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