Chatumal Perera, Sharada Amarakoon, Dulaj Weerakoon, Roshan Godaliyadda, and Parakrama Ekanayake
Indoor positioning, location based fingerprinting, acoustic localiza-tion, principal component analysis, clustering
Location based fingerprinting techniques have become a popular solution for indoor positioning due to their robust performance under non-line of sight and multipath conditions. This article introduces a novel method of constructing location based fingerprints using audible sound via principal component analysis for indoor positioning applications. A special parameter weighting technique is introduced here that warps the feature space to increase the inter-to intra-cluster distance while giving more priority to parameters with higher reliability. This article also extends this idea to gen- erate aggregated clusters that group existing clusters into umbrella clusters. This enables two phases of clustering. First an unknown location is matched to a region containing several grid points, after which the exact location is found within the region.
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