| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 528331 | Information Fusion | 2017 | 19 Pages |
•Corrected the description of the normal vectors in 2.1.2.•Added essential references.•Corrected typos, equation errors.•Polished the language.
This paper proposes a dead-reckoning (DR)/WiFi fingerprinting/magnetic matching (MM) integration structure that uses off-the-shelf sensors in consumer portable devices and existing WiFi infrastructures. One key improvement of this structure over previous DR/WiFi/MM fusion structures is the introduction of a three-level quality-control (QC) mechanism based on the interaction between different techniques. On QC Level #1, several criteria are applied to filter out blunders or unreliable measurements in each separate technology. Then, on Level #2, a threshold-based approach is used to set the weight of WiFi results automatically through the investigation of the EKF innovation sequence. Finally, on Level #3, DR/WiFi results are utilized to limit the MM search space and in turn reduce both mismatch rate and computational load. The proposed structure reduced the root mean square (RMS) of position errors in the range of 13.3 to 55.2% in walking experiments with two smartphones, under four motion conditions, and in two indoor environments. Furthermore, the proposed structure reduced the rate of mismatches (i.e., matching to an incorrect point that is geographically located over 15 m away from the true position) rate by over 75.0% when compared with previous DR/WiFi/MM integration structures.
