Marco Cimdins, M.Sc., BSEE
|Adresse||Fachhochschule Lübeck, Fachbereich Elektrotechnik und Informatik
Mönkhofer Weg 239
D-23562 Lübeck, Deutschland
|Telefon||+49 (0)451 300-5631|
Ich bin seit dem 1. Februar 2017 als wissenschaftlicher Mitarbeiter im Fachbereich Elektrotechnik und Informatik an der Fachhochschule Lübeck tätig. Mein Forschungsschwerpunkt liegt im Bereich der Lokalisation.
- Duales Studium mit integrierter Lehre (StudiLe) Elektrotechnik
- 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
- Wissenschaftlicher Mitarbeiter an der Fachhochschule Lübeck seit 2017
Aktivitäten in der Lehre
- Übungen: Bachelor ISE - Principles of Communication I
Artikel and Buchkapitel
|||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.
|||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.
|||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.
|||Modeling Received Signal Strength and Multipath Propagation Effects of Moving Persons , In 14th Workshop on Positioning, Navigation and Communication, 2017. [bib] [abstract]|
Device-free localization (DFL) systems detect and track persons without devices that participate in the localization process. A person moving within a target area affects the electromagnetic field that is measured by received signal strength (RSS) values. Consequently for DFL systems modeling of RSS is important and still an open issue. In this paper, we develop a simple model for prediction of RSS values in a setup with transmitter and receiver devices, a person and multipath propagation. We design and implement the model as a superposition of both, knife-edge diffraction to account for the change made by the person, and, propagation effects such as multipath propagation that result in reflection and path loss including the antenna characteristics. We evaluate our model in comparison with real measurements in various setups with and without multipath propagation. We achieve an accuracy that is close to our hardware limitations, which is the resolution of the measured RSS values of the receiver.
|||Investigation of Anomaly-based Passive Localization with IEEE 802.15.4 , Technical report, RWTH Aachen University, 2016. [bib] [pdf]|
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