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Publicação
Hybrid indoor localization system combining multilateration and fingerprinting
Orientador(es)
Resumo(s)
Indoor localization systems enable object tracking, e.g., related to retail, logistics and mobile robotics during their life cycle. This paper describes a real-world scenario implementation, based on Bluetooth Low Energy (BLE) beacons, evaluating a hybrid indoor positioning system (H-IPS) that combines two RSSI-based approaches: Multilateration (MLT) and Fingerprinting (FP). In addition, a Kalman Filter (KF) was employed to
decrease the positioning errors of both techniques. Furthermore a track-to-track fusion (TTF) is performed on the two KF outputs to maximize the performance. The results show that the accuracy of H-IPS overcomes the standalone FP in 21%, while the original MLT is outperformed in 52%. Finally, the proposed solution demonstrated a probability of error < 2 m of 80%, while the same probability for the FP and MLT were 56% and 20%, respectively.
Descrição
Palavras-chave
Fingerprinting Multilateration Indoor positioning system Kalman filtering Sensor fusion Bluetooth low energy
Contexto Educativo
Citação
de Oliveira, Leonardo; Rayel, Ohara; Leitao, Paulo (2022). Hybrid indoor localization system combining multilatration and fingerprinting. In the 48th Annual Conference of the IEEE Industrial Electronics Society (IECON’22). Brussels. p. 1-6
Editora
IEEE