Fingerprint location algorithm based on K-means for spatial farthest access point in Wi-Fi environment

摘要: The main problems of location fingerprint are the timeliness and accuracy location. However, huge database complex information will make process extremely time-consuming. On basis introducing basic idea strongest access point (AP), a fingerprints recognition algorithm based on K-means clustering farthest spatial AP Wi-Fi is proposed. This improves traditional algorithm, chooses optimal initial centres longest distance in space, optimises by using improved to complete rough position. Then, weight coefficients introduced into Euclidean weighted k-nearest neighbour enhance contribution achieve accurate algorithm. simulation results show effectiveness not only effectively reduces time number matched fingerprints, but also computational complexity negative impact real-time positioning system.