A Novel Fused Positioning Feature for Handling Heterogeneous Hardware Problem

Abstract

Received signal strength (RSS) in Wi-Fi networks is commonly employed in indoor positioning systems; however, variations in hardware challenge robustness of this approach. This paper proposes a novel positioning feature, which is called delta-fused principal strength (DFPS), to enhance the robustness of Wi-Fi localization against the problem of heterogeneous hardware. The proposed algorithm computes the pairwise delta RSS and then integrates with RSS using principal component analysis. This paper makes two principal contributions: First, the fused positioning feature embeds discriminative power within delta RSS to compensate for the problem of heterogeneous devices in a unified framework, and second, DFPS provides increased flexibility in determining the number of required components and achieves better computational efficiency. We applied DFPS to location fingerprinting systems in a realistic indoor Wi-Fi environment. Experimental results demonstrate the effectiveness of proposed algorithm, where DFPS outperforms previous robust positioning features for heterogeneous and homogeneous devices.