Abstract
This paper proposes a fingerprint-based indoor localization method, named FPFE (fingerprint feature extraction), to locate a target device (TD) whose location is unknown. Bluetooth low energy (BLE) beacon nodes (BNs) are deployed in the localization area to emit beacon packets periodically. The received signal strength indication (RSSI) values of beacon packets sent by various BNs are measured at different reference points (RPs) and saved as RPs’ fingerprints in a database. For the purpose of localization, the TD also obtains its fingerprint by measuring the beacon packet RSSI values for various BNs. FPFE then applies either the autoencoder (AE) or principal component analysis (PCA) to extract fingerprint features. It then measures the similarity between the features of PRs and the TD with the Minkowski distance. Afterwards, k RPs associated with the k smallest Minkowski distances are selected to estimate the TD’s location. Experiments are conducted to evaluate the localization error of FPFE. The experimental results show that FPFE achieves an average error of 0.68 m, which is better than those of other related BLE fingerprint-based indoor localization methods.
Highlights
Indoor localization is a procedure of locating or positioning a target device (TD) in indoor environments, such as buildings, houses, stores, and factories
This paper proposes a fingerprint-based indoor localization method, named fingerprint feature extraction (FPFE), using the Bluetooth low energy (BLE) technology
Under the scenario of 187 grid RPS, FPFE using AE feature extraction (FPFE-AE) is more stable than FPFE-principal component analysis (PCA), as FPFE-AE usually has smaller variances
Summary
Indoor localization is a procedure of locating or positioning a target device (TD) in indoor environments, such as buildings, houses, stores, and factories. It has become an important aspect in wide-scale applications including the health, industry, commerce, surveillance, and various sectors [1]. In the health sector, indoor localization can help the elderly, the handicapped and the visually impaired to navigate inside the hospital [2] In another example, indoor localization can be used for assisting living applications like behavioral monitoring and fall detection for elderly people and disabilities [3].
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