To address the difficulties of multi-source positioning coordination
delayed cross-scenario handover
and insufficient service continuity in complex indoor environments such as large commercial complexes
a large language model assisted scheduling and continuity control method for indoor multi-source positioning was proposed inspired by the 3GPP positioning framework and extended at the platform level. Cellular and Wi-Fi measurements were primarily aggregated on the location service platform
with extensible adaptation to Bluetooth/UWB and inertial sensing data. Dynamic source selection was achieved through spatio-temporal alignment
signal semantic encoding
scenario recognition
constrained scheduling
and fusion calculation. The method was evaluated with field data collected from eight floors of a 400 000 m² commercial complex. The results showed that the weighted scenario recognition accuracy reached 94.3%
the root mean square error in open LOS atrium scenarios was 0.75 m
the cross-scenario positioning continuity reached 88%
and the average positioning error was reduced by 49.5% compared with the fixed-weight fusion method. The proposed method improves the continuity
stability
and cross-scenario adaptability of indoor positioning services.
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references
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