Only one localization algorithm indoor environment has certain error, and the change of localization environment will cause instability of positioning system. The fusion of the position fingerprint matching algorithm and the polynomial distribution model can reduce the influence of the low positioning accuracy caused by the shortcomings of the polynomial distribution model and the position fingerprint matching model. In this paper, the position fingerprint matching algorithm and the polynomial distribution algorithm are respectively used to locate in different environments, and the same parameter is used to quantify the positioning results of the two different algorithms on the same environment. According to the selection coefficient, the optimal algorithm is selected for indoor positioning. In the online positioning stage, an algorithm that can be selected according to the selection coefficient to adapt to the environment can be used to locate. This adaptive algorithm can solve the respective defects of the fingerprint matching algorithm and the polynomial distribution model, and improve the indoor positioning accuracy.
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