A benchmarking measurement campaign in GNSS-denied/challenged indoor/outdoor and transitional environments

Abstract

Localization in GNSS-denied/challenged indoor/outdoor and transitional environments represents a challenging research problem. This paper reports about a sequence of extensive experiments, conducted at The Ohio State University (OSU) as part of the joint effort of the FIG/IAG WG on Multi-sensor Systems. Their overall aim is to assess the feasibility of achieving GNSS-like performance for ubiquitous positioning in terms of autonomous, global, preferably infrastructure-free positioning of portable platforms at affordable cost efficiency. In the data acquisition campaign, multiple sensor platforms, including vehicles, bicyclists and pedestrians were used whereby cooperative positioning (CP) is the major focus to achieve a joint navigation solution. The GPSVan of The Ohio State University was used as the main reference vehicle and for pedestrians, a specially designed helmet was developed. The employed/tested positioning techniques are based on using sensor data from GNSS, Ultra-wide Band (UWB), Wireless Fidelity (Wi-Fi), vison-based positioning with cameras and Light Detection and Ranging (LiDAR) as well as inertial sensors. The experimental and initial results include the preliminary data processing, UWB sensor calibration and Wi-Fi indoor positioning with room-level granularity and platform trajectory determination. The results demonstrate that CP techniques are extremely useful for positioning of platforms navigating in swarms or networks. A significant performance improvement in terms of positioning accuracy and reliability is achieved. Using UWB, decimeter-level positioning accuracy is achievable under typical conditions, such as normal walls, average complexity buildings, etc. Using Wi-Fi fingerprinting, success rates of approximately 97 % were obtained for correctly detecting the room-level location of the user.

Experimental Assessment of UWB and Vision-Based Car Cooperative Positioning System

“…Previous work of the authors has focused on the use of ultra-wide band (UWB) [1], wireless fidelity (Wi-Fi) [2], vision-based positioning with cameras and light detection and ranging (LiDAR) [3], as well as inertial sensors in different scenarios in GNSS-denied and challenged combined outdoor/indoor and transitional environments. Retscher et al [1] provide a comprehensive summary of the test scenarios and experimental sensor setups used in an one-week data collection campaign carried out at The Ohio State University (OSU), under the joint IAG (International Association of Geodesy) and FIG (Federation of Surveyors) working group (WG) on multi-sensor systems. Several scenarios are described for localisation and navigation of mobile sensor platforms, including vehicles, bicyclists, and pedestrians.…”

Fundamental Concepts and Evolution of Wi-Fi User Localization: An Overview Based on Different Case Studies

“…A Multivariate Gaussian Mixture Model (MVGMM) is fitted to model the probability distribution of RSS measurements in each cell to account for spatial correlation of the RSSs from multiple APs. Successful matching rates for mobile user tracking of over 98% were achieved for the allocation of the correct cell if a user walks along trajectories through rooms in a building [ 81 ].…”

Indoor Navigation and Mapping: Performance Analysis of Uwb-Based Platform Positioning

“…A number of NLOS issues are caused by objects which are part of the static environment in the area, such as walls, furniture. The impact of static, spatially inhomogeneous structures on RF signal propagation can be assessed by means of a calibration procedure, which typically ensures also a positioning performance improvement in the areas where NLOS issues are more apparent (Retscher et al, 2020).…”