Abstract
Indoor positioning technology plays an important role in the production and life of today's society. Modern people's clothing, food, housing, and transportation are increasingly closely related to Location Based Service. In this paper, an indoor location algorithm based on the radio frequency fingerprint matching is offered. In the offline phase, by deploying a small number of radio signal intensity location regions, the location selection mechanism is used to predict the location of mobile terminals, which can avoid the instability of radio frequency signals caused by time-lapse and the impact of changes in Access Point (AP) facilities. In the online stage, the location engine receives real-time Radio Frequency fingerprints and updates the fingerprint location by mapping time and equipment. Finally, several main localization algorithms are simulated and compared to the aspect of location accuracy. The proposed new method reduces the location error, improves the location accuracy by 1 to 2 meters, and achieves 100% within 2.5 meters.
Highlights
At present, indoor positioning technology [1], [2] has been applied in many industries, such as navigation, medical, pension, industrial manufacturing, warehouse, and logistics, and the improvement in service level and management efficiency is obvious
This is an improved clustering method of K Nearest Neighbor (KNN), which compares the distance between real-time received signals and fingerprint signals based on Euclidean distance
The Naive Bayes (Bayes) indoor location algorithm ignores the correlation between the signals of each wireless access point, which eventually leads to the decrease of positioning accuracy
Summary
Indoor positioning technology [1], [2] has been applied in many industries, such as navigation, medical, pension, industrial manufacturing, warehouse, and logistics, and the improvement in service level and management efficiency is obvious. A NEW INDOOR LOCATION ALGORITHM BASED ON THE RADIO FREQUENCY FINGERPRINT MATCHING A.
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