Indoor Positioning using the IEEE 802.11 Infrastructure

We propose a new indoor localization method which can be used to track a mobile node . Our method uses only the received signal strengths as input information . In addition our approach doesn't require any prior knowledge of the mobile node's motion and therefore doesn't use a cinematic motion model for tracking the mobile node. We discuss in detail the features of our approach and its resulting algorithm .We evaluate the performances of our algorithm using a real signal map

A Particle Filter Localisation System for Indoor Track Cycling Using an Intrinsic Coordinate Model

© 2018 ISIF In this paper we address the challenging task of tracking a fast-moving bicycle, in the indoor velodrome environment, using inertial sensors and infrequent position measurements. Since the inertial sensors are physically in the intrinsic frame of the bike, we adopt an intrinsic frame dynamic model for the motion, based on curvilinear dynamical models for manoeuvring objects. We show that the combination of inertial measurements with the intrinsic dynamic model leads to linear equations, which may be incorporated effectively into particle filtering schemes. Position measurements are provided through timing measurements on the track from a camera-based system and these are fused with the inertial measurements using a particle filter weighting scheme. The proposed methods are evaluated on synthesised cycling datasets based on real motion trajectories, showing their potential accuracy, and then real data experiments are reported

Uncoupled GPS Road Constrained Positioning based on Constrained Kalman Filtering

Car navigation systems take advantage of the synergies between the Global Positioning System (GPS) and digital road maps. For this kind of applications the digital road maps can provide a priori information to improve the positioning accuracy. This paper presents a method for the estimation of the user’s position, based on GPS positioning estimates, constrained to a road map. A low-cost GPS receiver was assumed as being the source of the positioning information. The techniques used in the proposed estimator were developed taking in consideration that the platforms where typically they would be implemented are characterized by having reduced computational capabilities. The algorithm’s positioning accuracy was characterized based on real data from a low-cost GPS receiver installed in a car. Different scenarios were used in the field trials in order to evaluate the impact of the satellite constellation visibility and geometry in the algorithm’s performance

Evaluating indoor positioning systems in a shopping mall : the lessons learned from the IPIN 2018 competition

The Indoor Positioning and Indoor Navigation (IPIN) conference holds an annual competition in which indoor localization systems from different research groups worldwide are evaluated empirically. The objective of this competition is to establish a systematic evaluation methodology with rigorous metrics both for real-time (on-site) and post-processing (off-site) situations, in a realistic environment unfamiliar to the prototype developers. For the IPIN 2018 conference, this competition was held on September 22nd, 2018, in Atlantis, a large shopping mall in Nantes (France). Four competition tracks (two on-site and two off-site) were designed. They consisted of several 1 km routes traversing several floors of the mall. Along these paths, 180 points were topographically surveyed with a 10 cm accuracy, to serve as ground truth landmarks, combining theodolite measurements, differential global navigation satellite system (GNSS) and 3D scanner systems. 34 teams effectively competed. The accuracy score corresponds to the third quartile (75th percentile) of an error metric that combines the horizontal positioning error and the floor detection. The best results for the on-site tracks showed an accuracy score of 11.70 m (Track 1) and 5.50 m (Track 2), while the best results for the off-site tracks showed an accuracy score of 0.90 m (Track 3) and 1.30 m (Track 4). These results showed that it is possible to obtain high accuracy indoor positioning solutions in large, realistic environments using wearable light-weight sensors without deploying any beacon. This paper describes the organization work of the tracks, analyzes the methodology used to quantify the results, reviews the lessons learned from the competition and discusses its future

Optimisation of Mobile Communication Networks - OMCO NET

The mini conference “Optimisation of Mobile Communication Networks” focuses on advanced methods for search and optimisation applied to wireless communication networks. It is sponsored by Research & Enterprise Fund Southampton Solent University. The conference strives to widen knowledge on advanced search methods capable of optimisation of wireless communications networks. The aim is to provide a forum for exchange of recent knowledge, new ideas and trends in this progressive and challenging area. The conference will popularise new successful approaches on resolving hard tasks such as minimisation of transmit power, cooperative and optimal routing