Information Aided Navigation: A Review

The performance of inertial navigation systems is largely dependent on the stable flow of external measurements and information to guarantee continuous filter updates and bind the inertial solution drift. Platforms in different operational environments may be prevented at some point from receiving external measurements, thus exposing their navigation solution to drift. Over the years, a wide variety of works have been proposed to overcome this shortcoming, by exploiting knowledge of the system current conditions and turning it into an applicable source of information to update the navigation filter. This paper aims to provide an extensive survey of information aided navigation, broadly classified into direct, indirect, and model aiding. Each approach is described by the notable works that implemented its concept, use cases, relevant state updates, and their corresponding measurement models. By matching the appropriate constraint to a given scenario, one will be able to improve the navigation solution accuracy, compensate for the lost information, and uncover certain internal states, that would otherwise remain unobservable.Comment: 8 figures, 3 table

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

An Unscented Kalman Filter-based Synchronization Control Approach for Communication-Based Train Control Systems

Communication-based train control (CBTC) system is an advanced train signalling and control technology which is developed using the moving block signalling (MBS) framework. The CBTC system has been shown to be capable of improving the operational efficiency, line capacity and safety of the railway operation. The main objective in implementing the MBS framework in CBTC system is to minimize the train headways through the utilization of an inter-train continuous communication system that determine and control the position of each train more precisely. One important challenge in such an implementation is the fulfillment of the necessary requirement of having highly accurate train localization method to ensure the safety of the short headway operation. This paper describes the results from experimental examination and application of a synchronization control strategy for the CBTC system using an unscented Kalman filter (UKF)-based sensor fusion approach as the localization method. In the proposed approach, the train localization task is performed using an UKF-based sensor fusion method which fuses measurement data from speed sensors and radio frequency identification tags. A synchronization control approach to ensure the safety movement of the train convoy in curved railway tracks under the MBS scheme is then proposed. The results presented in this paper show that the proposed localization and synchronization control methods can significantly improve the localization accuracy and reduce the inter-train headways

Algorithms for Autonomous Personal Navigation Systems

Personal positioning is a challenging topic in the area of navigation mainly because of the cost, size and power consumption constraints imposed on the hardware. Satellite based positioning techniques can meet the requirements for many applications, but cover well only outdoor environment. Problems like weak satellite signals make the positioning impossible indoors. Urban canyons are also difficult areas for GNSS based navigation because of large multipath errors and satellite signal outages. Many applications require seamless positioning in all environments. However, there is no overall solution for navigation in GNSS denied environment, which is reliable, accurate, cost effective and quickly installed. Recently developed systems for indoor positioning often require pre-installed infrastructure. Another approach is to use fully autonomous navigation systems based on self-contained sensors and street or indoor maps. This thesis is concerned with autonomous personal navigation devices, which do not rely on the reception of external information, like satellite or terrestrial signals. The three proposed algorithms can be integrated into personal navigation systems. The first algorithm computes positioning for a map aided navigation system designed for land vehicles traveling on road network. The novelty is in application of particle filtering to vehicle navigation using road network database. The second algorithm is aimed at map aided vehicle navigation indoors. The novelty is in the method for correction of position and heading. The third algorithm computes solution for pedestrian navigation system, which is based on body mounted inertial measurement unit and models of human gait

New Approach of Indoor and Outdoor Localization Systems

Accurate determination of the mobile position constitutes the basis of many new applications. This book provides a detailed account of wireless systems for positioning, signal processing, radio localization techniques (Time Difference Of Arrival), performances evaluation, and localization applications. The first section is dedicated to Satellite systems for positioning like GPS, GNSS. The second section addresses the localization applications using the wireless sensor networks. Some techniques are introduced for localization systems, especially for indoor positioning, such as Ultra Wide Band (UWB), WIFI. The last section is dedicated to Coupled GPS and other sensors. Some results of simulations, implementation and tests are given to help readers grasp the presented techniques. This is an ideal book for students, PhD students, academics and engineers in the field of Communication, localization & Signal Processing, especially in indoor and outdoor localization domains

Vision-based localization methods under GPS-denied conditions

This paper reviews vision-based localization methods in GPS-denied environments and classifies the mainstream methods into Relative Vision Localization (RVL) and Absolute Vision Localization (AVL). For RVL, we discuss the broad application of optical flow in feature extraction-based Visual Odometry (VO) solutions and introduce advanced optical flow estimation methods. For AVL, we review recent advances in Visual Simultaneous Localization and Mapping (VSLAM) techniques, from optimization-based methods to Extended Kalman Filter (EKF) based methods. We also introduce the application of offline map registration and lane vision detection schemes to achieve Absolute Visual Localization. This paper compares the performance and applications of mainstream methods for visual localization and provides suggestions for future studies.Comment: 32 pages, 15 figure

Feasibility of Onboard Smartphones for Railway Track Geometry Estimation: Sensing Capabilities and Characterization

The performance and sensitivity of smartphone sensors developed rapidly in recent years. Due to their accessibility and low costs compared to other industrial solutions, the use of smartphone sensors has become more and more common. In this article, the validity and reliability of a smartphone application in railway track geometry estimation are tested on a conventional rail line. This work focused on Galaxy S-series smartphones of Samsung and proposes an evaluation of the onboard sensing capabilities of their inertial sensors with the comparison of synchronous measurements by a multi-functional Track Recording Vehicle equipped with a contactless Track Geometry- (TGMS), and a Vehicle Dynamic Measuring System (VDMS). The raw accelerometer recordings showed a high-degree correlation with VDMS in both signal magnitude and waveform. The accuracy of gyroscope angular tracking in heading and pitching angle calculation was in the range of 0.2°–0.6°, which allowed the acceptable estimation of the central angle and the radius of horizontal curves. Based on the kinematic analysis techniques, the roll flexibility coefficient of the vehicle was determined, which allowed calculating the cross-level and the twist of the track. Furthermore, the local extreme values of the roll-rate gyro correlate with the isolated track geometry defects of the track twist gathered by TRV’s TGMS. Despite its limitations, the application of smartphones represents a prospective technological opportunity to explore new approaches and support rail asset management