Semi-Automated Signal Surveying Using Smartphones and Floorplans

Abstract

Abstract-Location fingerprinting locates devices based on pattern matching signal observations to a pre-defined signal map. This paper introduces a technique to enable fast signal map creation given a dedicated surveyor with a smartphone and floorplan. Our technique (PFSurvey) uses accelerometer, gyroscope and magnetometer data to estimate the surveyor's trajectory post-hoc using Simultaneous Localisation and Mapping and particle filtering to incorporate a building floorplan. We demonstrate conventional methods can fail to recover the survey path robustly and determine the room unambiguously. To counter this we use a novel loop closure detection method based on magnetic field signals and propose to incorporate the magnetic loop closures and straight-line constraints into the filtering process to ensure robust trajectory recovery. We show this allows room ambiguities to be resolved. An entire building can be surveyed by the proposed system in minutes rather than days. We evaluate in a large office space and compare to state-of-the-art approaches. We achieve trajectories within 1.1 m of the ground truth 90% of the time. Output signal maps well approximate those built from conventional, laborious manual survey. We also demonstrate that the signal maps built by PFSurvey provide similar or even better positioning performance than the manual signal maps.

A Survey of Magnetic-Field-Based Indoor Localization

“…PFSurvey was proposed in [80] for the rapid creation of signal maps that could be used to survey an entire building in a matter of minutes. The method uses accelerometer, gyroscope, and magnetometer data to estimate the surveyor's trajectory and uses SLAM and particle filters to incorporate a floor plan of the building, achieving trajectories within 1.1 m of ground truth in 90% of the time.…”

Analysis of Magnetic Field Measurements for Indoor Positioning

“…For example, the works [ 37 , 38 , 39 ] used crowdsourcing to merge sensor data from multiple users on different paths to build a magnetic map. PFSurvey [ 40 ] uses accelerometer, gyroscope, and magnetometer data to estimate the trajectory of the surveyor and uses SLAM and particle filters to incorporate the floor plans of buildings, allowing for the rapid construction of magnetic field maps. PFSurvey’s data collection costs are low, yet it achieves similar accuracy to traditional site survey methods.…”

A New RSS Fingerprinting-Based Location Discovery Method Under Sparse Reference Point Conditions

“…If the error caused by the interference cannot be corrected in time, the generated cumulative positioning error would affect the location estimation accuracy in the iteration. The particle filtering (PF) [39] algorithm is a state-equation-based method which has been proved to be suitable for solving the nonlinear filtering problem. The filtered result of the PF algorithm can be expressed by (17),…”