Leveraging Logical Anchor into Topology Optimization for Indoor Wireless Fingerprinting

The indoor subarea localization is of great significance in the application of dynamic hot-zone identification, indoor layout optimization, store dynamic pricing and crowd flow trend prediction. The ubiquitous mobile devices provide the opportunity for wireless fingerprinting-based indoor localization services. However, there are two places where the existing methods have been criticized. One is a tagging approach that requires a large number of professional surveys, with too much overhead wireless fingerprint construction and the weakened system scalability. The other is the crowdsourcing fingerprint-based methods meet the cold start problem in the initial stage of the operation. To attack these problems, the paper proposes a topology optimization approach with dynamic logical anchor selection for a subarea localization system. First of all, taking advantage of the feedback selection of logic anchor, a new annular-based radio map construction strategy is presented. The implementation of this strategy harnesses the characteristics of the indoor building structure and inter-subarea overlapping recognition, without depending on the topology and distribution of physical anchor (e.g., Access points or POIs). Secondly, exploiting the probabilistic support vector machine algorithm, the target is localized in the corresponding subarea in real-time pattern. Furthermore, the localization error is used to calibrate the localization result with an error recognition algorithm. Finally, massive experiments and simulations are implemented on a prototype system. The results show that the proposed method can decrease the human effort and computing cost and achieve higher localization accuracy compared with the existing approaches.