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We examined UWB-based indoor location in conjunction with a fingerprinttechnique in this work. We built a connection between the measured and realdistances for the UWB indoor positioning system. This connection is used toproduce a distance database that may be used to generate fringerprints. Wecreated a BP neural network to classify the target node to the relevantfringerpint using the distance database. Our suggested deep learning technologyconsiderably enhances location accuracy when compared to existing trilaterationsystems.

Precise Indoor Positioning Based on UWB and Deep Learning