Radio Map Recovery and Noise Reduction Method for Green WiFi Indoor Positioning System Based on Inexact Augmented Lagrange Multiplier Algorithm

摘要

Currently, WiFi indoor positioning system based on IEEE 802.11 is widely attractive for its free infrastructure and high localization performance. However, due to working on-demand strategy in green WiFi scenario, the access points are not always available for mobile when radio map is built in the offline phase. Radio map with unknown received signal strength is not valid for positioning and usually be replaced by the minimum value, which leads to poor positioning performance. In This paper we propose a radio map recovery method based on inexact augmented Lagrange multiplier (IALM) algorithm, which achieves to precisely recover the missing received signal strength in the radio map for those access points unavailable in the offline. By solving the nuclear norm minimization, the IALM algorithm could not only recover the missing received signal strength, but also reduce the noise effectively. We have implemented the proposed method in our lab and evaluated its performances. The experiment results indicate the proposed method could precisely recover the radio map and achieve good positioning performance.