Abdelmoumen Norrdine

Position estimation using artificial generated magnetic fields

A positioning system is introduced which overcomes the limitations of existing indoor positioning systems by the use of artificial quasi static magnetic fields. The proposed DC magnetic signals show no special multipath effects and have excellent characteristics for penetrating various obstacles. In this contribution the theory of coil-based magnetic fields as well as the basic function principle of the positioning system are described. Furthermore, a prototype that is currently under development is presented.

A robust and precise 3D indoor positioning system for harsh environments

In recent years there has been a considerable research on the development of indoor positioning systems. Several kinds of technologies such as ultrasonic, UWB, WLAN, optical waves and hybrid solutions were utilized already. However, using these technologies many difficulties arise in indoor environments due to none line of sight (NLoS) and multipath errors. In this paper, the realization and the evaluation of a 3D indoor localization system, which is robust for harsh and NLoS environments is presented. The positioning system is Direct Current (DC) magnetic based, shows no multipath effects and has excellent characteristics for penetrating various obstacles. To eliminate additional interference fields (e.g. earths magnetic field, electrical disturbances) a differential measurement principle and adaptive noise suppression algorithms are used. In the case of the deployment in smaller areas, even smart phones equipped with embedded low cost sensors can be utilized as mobile station. A real time 3D position estimation with an accuracy up to 50 cm is achievable by setting up only three magnetic coils inside or around the building. In order to analyze existing systematic errors, a simple calibration procedure has been implemented. The calibration routine reduces the systematic errors, which leads to improved systems positioning accuracy up to 10 cm.

An IMU/magnetometer-based Indoor positioning system using Kalman filtering

Many infrastructure-based indoor positioning technologies such as UWB, WLAN, ultrasonic or infrared are limited by disturbances and errors caused by building objects (e.g. walls, ceiling and furniture). Magnetic fields, however, are able to penetrate various obstacles - in this case commonly used (building) materials - without attenuation, fading, multipath or signal delay. Thus, in the past years a DC Magnetic signal based Indoor Local Positioning System (MILPS), which consists of multiple electrical coils as reference stations and tri-axial magnetic sensors as mobile stations was developed. By observing magnetic field intensities of at least three different magnetic coils, position estimation of the magnetic sensors can be carried out even in severe indoor environments. However, the positioning algorithm currently used is designed for stop-and-go localization. This contribution focuses on the integration of a low cost Inertial Measurement Unit (IMU) in order to improve the systems positioning update rate and therefore provide complete 2D localization estimates for kinematic applications and probably afford position solutions even outside the coverage area of MILPS. Therefore an Extended Kalman-Filter (EKF) is adapted for position estimation. The filtering process is accomplished in two steps. The first step leads to position prediction caused by inertial data, which could be updated at the second step by using the MILPS-measurements. In this context simulations combining MILPS and IMU have been performed. Testing of the filter with real IMU-data and simulated MILPS positioning data delivered promising results for indoor positioning purposes.

Building information systems based on precise indoor positioning

During the last 10 years, many modern IT-based applications have developed inside buildings. Many of those applications would benefit by the ability to locate people and/or objects inside the building (indoor positioning). However, most of todays indoor positioning systems are not able to deliver precise position information (<10 cm) along with quality parameters. Ultra wide band (UWB) is a new radio-based technology that allows the determination of distances in indoor environments with a very high spatial resolution even through building materials. At the Institute of Geodesy of TU Darmstadt, a high-resolution UWB positioning system (UWB-ILPS; ILPS, indoor local positioning systems) based on trilateration principle has been developed to estimate the position of a mobile station precisely. To benefit from knowing the position and orientation, it is necessary to select and merge data linked to the users location for indoor location services. By this means, the visitor to a public building may benefit from the system as his position is shown on a digital floor plan generated dynamically or by retrieving location-based information inside the building. Mixed reality systems also offer advantages for a mobile building information system. For this purpose, a webcam was replaced by the digital camera in the UWB-ILPS prototype. Knowing the cameras location in space and its view direction, one is able to merge the real world taken by the webcam with the virtual world represented by a 3D CAD model of the building.

IMU/magnetometer based 3D indoor positioning for wheeled platforms in NLoS scenarios

In recent years the research on localization and navigation systems in GNSS-denied environments has been focused from both industry and research. Although many technologies based on e.g. UWB, WLAN, ultrasonic or infrared have been utilized, there is still no final solution for position and orientation determination in indoor areas. The fact, that applied signals in common approaches are influenced by fading and multipath inside buildings leads to restrictions on line-of-sight (LoS) conditions. In contrast, the ability of penetrating any kind of building materials qualifies magnetic fields to realize object positioning in harsh indoor environments. Hence, a DC Magnetic signal based Indoor Local Positioning System (MILPS) has been developed consisting of multiple electrical coils, representing reference stations. Based on the magnetic field intensities of at least three different coils, the corresponding slope distances and therefore the observers position can be estimated. Facing kinematic purposes a combination of MILPS and an Inertial Measurement Unit (IMU) has been applied, utilizing methods of sensor fusion. Observed inertial data - in this case three dimensional acceleration and angular rate measurements - lead to the sensors relative motion changes, which are processed by kinematic motion models. Based on a discrete integration with respect to the measurement time interval, the sensors current state - consisting of position, velocity and orientation - can be predicted. These high-frequency derived predictions are furthermore supported by external MILPS-distances and elevation angles utilizing methods of Kalman Filter. Focus in this contribution lies on the processing of both inertial data and magnetic field measurements for three dimensional applications.

Accurate 3D Positioning for a Mobile Platform in Non-Line-of-Sight Scenarios Based on IMU/Magnetometer Sensor Fusion

In recent years, a variety of real-time applications benefit from services provided by localization systems due to the advent of sensing and communication technologies. Since the Global Navigation Satellite System (GNSS) enables localization only outside buildings, applications for indoor positioning and navigation use alternative technologies. Ultra Wide Band Signals (UWB), Wireless Local Area Network (WLAN), ultrasonic or infrared are common examples. However, these technologies suffer from fading and multipath effects caused by objects and materials in the building. In contrast, magnetic fields are able to pass through obstacles without significant propagation errors, i.e. in Non-Line of Sight Scenarios (NLoS). The aim of this work is to propose a novel indoor positioning system based on artificially generated magnetic fields in combination with Inertial Measurement Units (IMUs). In order to reach a better coverage, multiple coils are used as reference points. A basic algorithm for three-dimensional applications is demonstrated as well as evaluated in this article. The established system is then realized by a sensor fusion principle as well as a kinematic motion model on the basis of a Kalman filter. Furthermore, a pressure sensor is used in combination with an adaptive filtering method to reliably estimate the platform’s altitude.

Platform Architecture for Decentralized Positioning Systems

A platform architecture for positioning systems is essential for the realization of a flexible localization system, which interacts with other systems and supports various positioning technologies and algorithms. The decentralized processing of a position enables pushing the application-level knowledge into a mobile station and avoids the communication with a central unit such as a server or a base station. In addition, the calculation of the position on low-cost and resource-constrained devices presents a challenge due to the limited computing, storage capacity, as well as power supply. Therefore, we propose a platform architecture that enables the design of a system with the reusability of the components, extensibility (e.g., with other positioning technologies) and interoperability. Furthermore, the position is computed on a low-cost device such as a microcontroller, which simultaneously performs additional tasks such as data collecting or preprocessing based on an operating system. The platform architecture is designed, implemented and evaluated on the basis of two positioning systems: a field strength system and a time of arrival-based positioning system.

Accurate 3D UWB radar super-resolution imaging for a bi-static antenna configuration

This paper deals with a real-time capable accurate 3D ultra-wideband radar imaging algorithm for complex shaped 3D objects including edges and corners. A well known wavefront based imaging algorithm is adapted to the bi-static 3D scenario which is, in contrast to the popular migration based algorithms, real-time capable and directly gathers the object contour coordinates. In order to reconstruct a accurate 3D object contour, the commonly proposed planar scan track (i.e. the planar aperture) of the antennas is modified and extended to a spatial scanning track with a circumnavigation of the object. To provide a more diverse radar signature the monostatic antenna configuration is extended to a bistatic configuration. Hence, the shape of the radiating wavefront is no longer spherical but ellipsoidal. Consequently, to ensure the super-resolution accuracy, the intersection point of 3 arbitrarily oriented and shifted ellipsoids in the 3 dimensional Euclidean space has to be determined. An iterative solution will be presented which utilizes the Gauss-Newton method to obtain a fast converging estimation with negligible error in the least-square sense. An experimental validation is carried out based on complex test objects with small shape variations relative to the used wavelength, an pseudo noise radar device (from 4.5 GHz to 13.5 GHz) and two tapered slot line Vivaldi antennas.