Dr.-Ing. Mathias Pelka
Ich war vom 1. Oktober 2013 bis zum 30. Juni 2018 als wissenschaftlicher Mitarbeiter im Fachbereich Elektrotechnik und Informatik an der Fachhochschule Lübeck tätig. Mein Forschungsschwerpunkt lag im Bereich der Ortung, drahtlosen Sensoren sowie der Modellbildung.
- Bachelorstudium: Internationaler Studiengang Elektrotechnik mit Abschluss Bachelor of Science der Fachhochschule Lübeck und Bachelor of Science Electrical Engineering der Milwaukee School of Engineering
- Masterstudium: Angewandte Informationstechnik der Fachhochschule Lübeck
- Promotion zum Dr.-Ing. mit der Arbeit: Analyse, Optimierung und systematischer Aufbau von Ortungssystemen
Aktivitäten in der Lehre
- Übungen: Bachelor ISE - Principles of Communication II
- Vorlesung: Master AIT - Drahtlose Netze in der Automation
- Vorlesung: Master AIT - Brückenkurs Kommunikationstechnik
- Reviewer für Computer Networks Journal - Elsevier
- Reviewer für Transactions on Aerospace and Electronic Systems - IEEE
- Organisation des zweiten KuVS Expert Talk on Localization
- Organisation des ersten KuVS Expert Talk on Localization
|||A new localization algorithm based on neural networks , In Proceedings of the 3rd KuVS/GI Expert Talk on Localization, 2018. [bib] [pdf] [abstract]|
Indoor localization plays a major role in a wide range of applications. To determine the location of a tag, localization algorithm is required. In the past, machine learning algorithms were difficult to implement in consumer hardware, but with the advent of tensor processing units, even smartphones are capable to use artificial intelligence to solve complex problems. In this paper, we investigate a machine learning algorithm based on neural networks and compare the result to a linear least squares estimator. We design and evaluate different neural networks. Based on our observation, the neural network delivers poor performance compared to the linear least squares estimator.
|||UWB-based Single Reference Point Positioning System , In ITG-Fachbericht-Mobilkommunikation VDE VERLAG GmbH, 2017. [bib] [abstract]|
Indoor positioning enables new applications, for instance monitoring of goods in smart factories. For such applications, indoor positioning requires cost-effective solutions with high accuracy. State-of-the-art positioning systems are expensive due to high infrastructure and maintenance costs. In this paper we suggest an accurate UWB-based single reference point positioning system using multiple antennas. We compare lateration and hyperbolic lateration as positioning methods and present efficient algorithms for UWB-based single reference point positioning systems. We present theoretical limits based on the Cramer-Rao lower bound and derive an error estimation as well as evaluation results. Our measurements indicate that decimeter accuracy is possible.
|||Survey of challenges and towards a unified architecture for location systems , In Journal of Network and Computer Applications, volume 67, 2016. [bib] [pdf] [abstract]|
Abstract Localization is a key aspect of emergent applications in the medical, industrial and consumer field. In this article we survey state of the art, identify current challenges and issues for localization systems and suggest a unified layered architecture. The analysis reveals that challenges cannot be addressed in an isolated manner for example, energy consumption is tied to the choice of algorithm and employed hardware. To separate various challenges and investigate them independently, we propose the concept of position providers. Position providers in the lower layers allow abstraction of positioning methods, positioning algorithms and positioning hardware. Thereby, a position provider encapsulates methods, algorithms and hardware. Furthermore, we suggest a classification of position providers inspired by related work. We propose a unified architecture for location systems which uses positioning and integration layers as main building blocks.
|||Iterative approach for anchor configuration of positioning systems , In ICT Express, volume 2, 2016. [bib] [pdf] [abstract]|
With anchor positions and measurements of distances between an object and anchors, positioning algorithms calculate the position of an object, e.g. via lateration. Positioning systems require calibration and configuration prior to operation. In the past, approaches employed reference nodes with GPS or other reference location systems to determine anchor positions. In this article, we propose an approach to determine anchor positions without prior knowledge. We evaluate our approach with simulations and real data based on the Decawave DW1000 radio and show that the error is proportional to the mean error of the distance estimation.
|||Minimizing Indoor Localization Errors for Non-Line-of-Sight Propagation , In International Conference on Localization and GNSS, 2018. [bib] [abstract]|
Indoor Localization becomes more important, as it provides additional context for many applications for example in the Internet of Things (IoT). Time-of-flight measurements, as a basis for distance estimation, are susceptible for non-line-of-sight (NLOS) propagation, resulting in large distance errors. Standard least squares solutions to estimate the targets location do not account for NLOS propagation which results in large scale errors. We investigate the difference between L1- and L2-minimization and present a new framework based on a modified RANSAC approach. Additionally, we investigate a Support Vector Machine (SVM) to detect NLOS measurements.We present simulation and measurement results and evaluate our approach. We show that our framework delivers better performance in presence of NLOS propagation compared to plain L1- or L2-minimization.
|||RF-Based Safety-Critical Hybrid Localization , In The Ninth International Conference on Indoor Positioning and Indoor Navigation (IPIN), 2018. [bib] [abstract]|
In safety-critical environments, e.g. paint or machine shops, precise knowledge of positions of persons is important. If an emergency is detected, e.g. a fire or an intruder in the safety-critical area of heavy machinery, emergency shutdown procedures are activated. This requires fine-grained localization with a tag-based localization system, where the person carries a tag. Without a person carrying a tag, precise localization and detection is difficult. In this paper, we propose a RF-based hybrid localization system for safety-critical localization that consists of two major components: a tag-based and device-free subsystem. The device-free subsystem provides coarse-grained localization and monitors a gate area, serving as an entrance towards the safety-critical area where fine-grained localization is required. We propose an architecture of the system, discuss our setup and evaluate typical use cases. Our preliminary evaluation demonstrates that our system detects the correct state of the hybrid localization system with an accuracy of 90%.
|||Sundew: Design and Evaluation of a Model-based Device-free Localization System , In The Ninth International Conference on Indoor Positioning and Indoor Navigation (IPIN), 2018. [bib] [abstract]|
The state-of-the-art in device-free localization systems based on RF-measurements is fingerprinting. Fingerprinting requires reference measurements called fingerprints that are recorded during a training phase. Especially in device-free localization systems, recording of reference measurements for fingerprinting is a tedious, costly, and error-prone task. In this paper, we propose Sundew, a model-based device-free localization system that does not need fingerprinting in the sense of reference measurements but is able to calculate signal strength values at any position and compare it to actual measurements after a simple calibration phase. Sundew — as any device-free localization system — requires a metric for comparison of feature vectors. In this paper, we investigate the influence of nine different distance metrics on the positioning accuracy. Simulations and measurements show that our suggested model-based device-free localization system works best with the L 1 distance metric. Sundew estimates 90% of positions in a 2.5m x 2.5m grid correctly, independent of the orientation of the person in the target area.
|||Optical Underwater Distance Estimation , In Oceans MTS/IEEE, 2017. [bib] [abstract]|
Data communication with high data rate and precise underwater positioning with an accuracy of several centimeters is a problem. Precise positioning is important for autonomous operation and helps conserve energy which is important for many tasks. State-of-the-art acoustic communication faces difficulties underwater, e.g. multipath fading or variation of propagation speed. In this work, we propose optical distance estimation, which is the foundation for positioning. We combine the Beer-Lambert law and the inverse-square-law to model the channel of the medium. We investigate different wavelengths and employ curve fitting based on the Levenberg-Marquardt algorithm to determine the unknown coefficients of the model e.g. absorption. Our evaluation shows promising results and distance estimation of up to 25~m is possible. In stream water we determined the mean error for the optical distance estimation of 0.04m.
|||S-TDoA - Sequential Time Difference of Arrival - A Scalable and Synchronization Free Approach for Positioning , In IEEE Wireless Communications and Networking Conference, 2016. [bib] [abstract]|
In the past various solutions for localization evolved to productive usage for wireless applications. These solutions are robust, precise and energy efficient. However, scalability, complexity and flexibility are still open issues. Especially, supported number of objects or update rates for localization are still limiting factors for the usage of the systems. In this work we suggest an approach called S-TDoA which stands for sequential Time Difference of Arrival that supports unlimited number of objects and high update rates. The key concept is a sequential triggering of anchors that send periodic messages. Tags determine their position by listening to the anchor messages and measuring time intervals. Additionally, this approach enhances security because tags are not visible as they do not send messages. We implement and evaluate S-TDoA in a localization system based on UWB-RF- Chips. The preliminary results demonstrate the advantages of our implementation regarding scalability and update rates as well as privacy.
|||Impact of Altitude Difference for Local Positioning Systems and Compensation with Two-Stage Filters , In 2016 International Conference on Localization and GNSS, 2016. [bib] [abstract]|
In range-based positioning systems, an altitude difference between tag and reference plane causes errors in two- and three-dimensional positioning. We analyze how these errors reduce accuracy of Local Positioning Systems (LPS) and show how compensation of the altitude difference improves performance of positioning. In this paper, we consider the availability of additional altitude information and transform the three-dimensional positioning problem into a two-dimensional problem. We provide algorithms for time-based positioning systems with a two-stage estimator for Two-Way Ranging and Time Difference of Arrival and incorporate additional altitude information. We simulate our approach for altitude difference compensation and provide an evaluation based on a Ultra-Wideband (UWB) radio with ranging capability and a barometric sensor for additional altitude information. A comparison is then made between our approach and standard solutions such as the Extended Kalman filter and the Unscented Kalman filter. Finally, the successful decrease in the positioning error for two- and three-dimensional positioning system, using the system disclosed herein, is illustrated. Based on our analysis, we derive practical solutions to deal with altitude differences for positioning systems.
|||Introduction, Discussion and Evaluation of Recursive Bayesian Filters for Linear and Nonlinear Filtering Problems in Indoor Localization , In The Seventh International Conference on Indoor Positioning and Indoor Navigation, 2016. [bib] [abstract]|
Linear and nonlinear filtering for state estimation (e.g. position estimation or sensor fusion) for indoor positioning and navigation applications is a challenging task. Sensor fusion becomes more important with cost-effective sensors being readily available. However, state estimation with recursive Bayesian filters for sensor fusion and filtering are difficult to apply. We present an overview for the general Bayesian filter and derive the most commonly used recursive Bayesian filters, namely the Kalman, extended Kalman and the unscented Kalman filter along with the particle filter. The later Kalman filters are extension of the original Kalman filter, which are able to solve nonlinear filtering problems. The particle filter is also able to solve nonlinear filtering problems. We evaluate the recursive Bayesian filters for linear and nonlinear filtering problems for sensor fusion from relative dead reckoning positioning data and absolute positioning data from an UWB positioning system. We discuss and evaluate performance and computational complexity and provide recommendations for the use case of the recursive Bayesian filters.
|||QRPos: Indoor Positioning System for Self-Balancing Robots based on QR Codes , In The Seventh International Conference on Indoor Positioning and Indoor Navigation, 2016. [bib]|
|||Investigation of Anomaly-based Passive Localization with Received Signal Strength for IEEE 802.15.4 , In The Seventh International Conference on Indoor Positioning and Indoor Navigation, 2016. [bib] [abstract]|
Localization has important applications, for instance intrusion detection and elderly care. Such applications benefit from Device-free passive (DfP) localization systems, which employ received signal strength measurements (RSSM) to detect and track entities that neither participate actively in the localization process nor emit signals actively. RSSMs include received signal strength indicator (RSSI), energy detection (ED) and link quality indicator (LQI) measurements. This paper compares different packet-based RSSMs for DfP localization and presents detection results of a DfP anomaly-based detection system employed by IEEE 802.15.4 compliant devices. Furthermore, we investigate techniques for anomaly detection with continuous RSSI measurements.
|||Indoor Localization based on Bi-Phase Measurements for Wireless Sensor Networks , In 2015 IEEE Wireless Communications and Networking Conference (WCNC): - Track 3: Mobile and Wireless Networks (IEEE WCNC 2015 - Track 3- Mobile and Wireless Networks), 2015. [bib] [abstract]|
Indoor localization is important for medical and industrial application as well as for wireless emergency and security systems. For such applications an accuracy within a few meters is desired. Available radio based systems within that accuracy are neither cost effective nor easy to deploy. In this work, we suggest an approach called biphase measurement based on phase measurements with two frequencies to determine the location of a tag. We design and build a complete indoor positioning system based on bi-phase measurements with easy to deploy wireless sensor nodes. The wireless sensor nodes shape anchors and tags and communicate results to a location engine of the indoor positioning system. Our implementation comprises lowcost IEEE802.15.4 radio chips with built-in support for phase measurements unit for both, anchor and tags. We compute the position of the tag based on distance estimation retrieved with bi-phase measurements. We evaluate our indoor positioning system providing first measurement results for accuracy and precision and discuss trade-off between scalability, real-time and accuracy.
|||Wireless Medical Sensors - Context, Robustness and Safety , In 49th annual conference of the German Society for Biomedical Engineering (BMT 2015), 2015. [bib]|
|||Accurate Radio Distance Estimation by Phase Measurements with Multiple Frequencies , In The Fifth International Conference on Indoor Positioning and Indoor Navigation 2014 (IPIN 2014), 2014. [bib] [abstract]|
Indoor localization is beneficial for logistics, industrial applications and for several consumer applications. In the area of logistics, e.g. warehouses, localization accuracy within a few meters is desired. Available radio based systems within that accuracy are neither cost effective nor easy to deploy. Distance estimations are one possible method for localization. In this work, we propose phase measurements between two wireless sensor nodes for distance estimation. We introduce a mathematical model to estimate distances from phase measurements with multiple frequencies and provide a systematic analysis of possible sources of errors. Additionally, we derive requirements, e.g. resolution and speed for a phase measurement unit to reach certain accuracy. To proof our theoretical results, we present evaluation results based on our implementation. Our implementation comprises a low cost IEEE 802.15.4 hardware with a built-in phase measurement unit. We implement the developed algorithm for distance estimation in our wireless sensor network and use two wireless sensor nodes to perform a phase measurement. The contribution of the paper comprises a new model for phase measurements to estimate distances and a preliminary evaluation with our hardware.
|||Evaluation of Radio Based, Optical and Barometric Localization for Indoor Altitude Estimation in Medical Applications , In The Fifth International Conference on Indoor Positioning and Indoor Navigation, 2014. [bib] [abstract]|
The advances of electronics provide options for improved monitoring of patients in clinical environment.Medical applications like blood pressure monitoring require precise and wireless altitude measurement in indoor environment. An error of only a few centimeters may lead to mistreatment of patients.Furthermore, user requirements like small form factor, usability and robust operation are important in the medical field.Existing evaluations of indoor localization systems focus on accuracy analysis of x- and y-coordinates and not on the z-coordinate (altitude). In this paper, we define evaluation criteria for altitude estimation in medical applications. We compare an Ultra-Wide-Band indoor localization system, an optical Microsoft Kinect camera system and our own development of a wireless barometric sensor against these criteria. We present a comparative measurement setup, results and a final evaluation of the three systems in an indoor environment.
|||Evaluation of time-based ranging methods: Does the choice matter? , In 14th Workshop on Positioning, Navigation and Communication, 2017. [bib] [abstract]|
Positioning is useful in a number of applications, for instance smart home, smart factory and health care applications. Time-based ranging methods for positioning are the state-of-the-art but require precise timestamping. Sophisticated ranging methods compensate sources of errors, for instance clock drift caused by a crystal or an asymmetrical measuring principle, to provide precise timestamping. So far, no comprehensive study of different time-based ranging methods using the same hardware and the same evaluation setup was carried out. Consequently, we discuss, implement and evaluate five time-based ranging methods, including Two-Way Ranging, Double Two-Way Ranging, Asymmetrical Double-Sided Two-Way Ranging, Symmetrical Double-Sided Two-Way Ranging and Burst Mode Symmetric Double-Sided Two-Way Ranging. We evaluate accuracy, precision, robustness and run time for the ranging methods and answer the question if the choice of the time-based ranging method matters.
|||Anomaly-based Device-free Localization with Particle Filtering , In Workshop on Dependable Wireless Communications and Localization for the IoT, 2017. [bib] [abstract]|
In the Internet of Things (IoT), devices, e.g. sensors or actuators, transmit packets to transfer data. For the IoT localization information is crucial, as it provides additional context for the data. We envision that devices in the IoT know their position and on receipt of a packet, the received signal strength is measured. This measurement is used to build a device-free localization (DFL) system to improve the dependability of the IoT system. DFL systems are able to detect and track persons within a target area that neither wear a device nor participate actively in the process of localization. This work presents an anomaly-based DFL system that measures if a person affects the radio frequency (RF) propagation and determines the position with a particle filter. In our 65m 2 indoor testbed, we employ eight IEEE 802.15.4 compliant wireless transceivers and estimate the position of a person with a median localization error of 1.4m.
|||Comparison of wired and wireless synchronization with clock drift compensation suited for U-TDoA localization , In 13th Workshop on Positioning, Navigation and Communication, 2016. [bib] [abstract]|
Indoor localization with Uplink Time Difference of Arrival (U-TDoA) provides good scalability, high updates rates and high accuracy. However, clock errors lead to localization errors and synchronization is important. In this paper, we design and implement wired and wireless synchronization and provide a comparison between them. We design and implement a wireless synchronization with clock drift compensation. For wired and wireless synchronization, we discuss reasons for clock deviation that lead to localization errors. We evaluate both approaches in a U-TDoA measurement setup. Finally, we provide recommendations for wired and wireless synchronization.
|||Mobile Robot Seamless Localization with Localization Optimized QR Codes , In 12th Workshop on Positioning, Navigation and Communication, 2015. [bib] [abstract]|
Indoor navigation is a prerequisite for new emerging applications for autonomous mobile robots. Additionally to the location of a robot, the orientation is important for these applications. Furthermore, a solution to this localization problem should be inexpensive and easy extensible for new areas of a building. We propose inexpensive optical landmarks based on localization optimized Quick Response (QR) code for localization of the landmark within an image to reduce computational cost. We further specify the error correction level, border, and size of the QR code for optimal localization. The proposed QR code combines GPS coordinates and local coordinates which allows seamless integration of our approach. We perform image processing to estimate the distance and orientation of a mobile robot with respect to the localization optimized QR code. To evaluate our approach we implemented the approach in an Android application and measured the performance in experiments. Additionally, we suggest a method to retrieve more accurate GPS information based on the measured orientation and distances. Our implementation achieves update rates of up to 3 Hz and an accuracy of 1 cm
|||Impact of the antenna orientation for distance estimation , Technical report, Technische Universität Braunschweig, 2018. [bib] [pdf] [abstract]|
Indoor localization is important for a wide range of use cases including industrial, medical and scientific applications. The location accuracy is affected by the localization algorithm and the quality of the measurements as input for the algorithm. Many indoor localization systems employ ultra-wideband distance measurements, as they offer high accuracy and are cost effective. One of the methods for distance measurement is twoway ranging. This paper investigates the impact of the antenna orientation on the distance measurement based on symmetrical double-sided two-way ranging. We show that up to 0.25m of the measurement error is attributed to the orientation of the antennas. We provide explanations and suggest solutions to reduce the effect.
|||S-TDoA (Sequential Time Difference of Arrival)-Verfahren zur Positionsermittlung von bewegbaren Objekten durch sequentielle Ankunftszeitdifferenzbestimmung von periodischen Signalen , EP Patent App. EP20,170,157,702 Google Patents, 2017. [bib] [pdf]|
|||Evaluation of Bluetooth Positioning for Medical Device Tracking , GRIN (T. M. Buzug et. al., ed.), 2017. [bib]|
|||Investigation of Anomaly-based Passive Localization with IEEE 802.15.4 , Technical report, RWTH Aachen University, 2016. [bib] [pdf]|
|||Proceedings of the 2nd KuVS Expert Talk on Localization , Technical report, RWTH Aachen University Department of Computer Science of RWTH Aachen University (Mathias Pelka, Grigori Goronzy, Jó Agila Bitsch Link, Horst Hellbrück, Klaus Wehrle, eds.), 2016. [bib] [pdf]|
|||Position Calculation with Least Squares based on Distance Measurements , Technical report, Fachhochschule Lübeck, 2015. [bib] [pdf] [abstract]|
Position estimation based on distances is a well understood problem. This document describes a simple way to linearize the position equation. Based on the linearization the problem is solved step by step using least squares. This paper includes an example implementation in Matlab.
|||Comparison and Performance Evaluation of Indoor Localization Algorithms based on an Error Model for an Optical System , GRIN (T. M. Buzug et. al., ed.), 2015. [bib]|
|||Proceedings of the 1st KuVS Expert Talk on Localization , Technical report, RWTH Aachen University Department of Computer Science of RWTH Aachen University (Mathias Pelka, Jó Agila Bitsch Link, Horst Hellbrück, Klaus Wehrle, eds.), 2015. [bib] [pdf]|