IWKNN: An Effective Bluetooth Positioning Method Based on Isomap and WKNN

Abstract EN

Recently, Bluetooth-based indoor positioning has become a hot research topic.

However, the instability of Bluetooth RSSI (Received Signal Strength Indicator) promotes a huge challenge in localization accuracy.

To improve the localization accuracy, this paper measures the distance of RSSI vectors on their low-dimensional manifold and proposes a novel positioning method IWKNN (Isomap-based Weighted K -Nearest Neighbor).

The proposed method firstly uses Isomap to generate low-dimensional embedding for RSSI vectors.

Then, the distance of two given RSSI vectors is measured by Euclidean distance of their low-dimensional embeddings.

Finally, the position is calculated by WKNN.

Experiment indicates that the proposed approach is more robust and accurate.