Sven Ole Schmidt, M.Sc.
|Adresse||Technische Hochschule Lübeck, Fachbereich Elektrotechnik und Informatik
Mönkhofer Weg 239
D-23562 Lübeck, Germany
|Phone||+49 (0)451 300-5740|
Seit dem 01. November 2018 bin ich wissenschaftlicher Mitarbeiter des Kompetenzzentrums Kommunikation - Systeme - Anwendungen (CoSA) der Technischen Hochschule Lübeck. Im Rahmen meiner Masterarbeit habe ich mich mit dem Feld der Ressourcenzuordnung in Multiplex-Broadcast-Signalen in Industrie 4.0-Umgebungen beschäftigt. Dabei habe ich einen latenzbasierten Scheduling-Algorithmus entwickelt. Ich interessiere mich für verteilte Systeme, Signalverarbeitung und das Forschungsgebiet der Algorithmik.
- Geboren am 15. Juni 1992
- Studium der Elektro-/Informationstechnik (B.Sc.) an der Universität Bremen bis 2015
- Studium der Vertiefung Informations- und Kommunikationstechnik (M.Sc) an der Universität Bremen bis 2018
- Seit dem 01. November 2018 Wissenschaftlicher Mitarbeiter am Kompetenzzentrum Kommunikation - Systeme - Anwendungen (CoSA)
|||MAMPI – Multipath-assisted Device-free Localization with Magnitude and Phase Information , In International Conference on Localization and GNSS, 2020. [bib] [abstract]|
Narrowband radio-frequency (RF)-based device-free localization (DFL) systems suffer from multipath propagation. Therefore, we propose multipath-assisted device-free localization with magnitude and phase information (MAMPI), a DFL system that employs ultra-wideband (UWB) channel impulse response (CIR) measurements between a transmitter and receiver and thereby benefits from multipath propagation. We implement a model that includes raytracing, diffraction, and inaccuracies of measurements in a validated error model. The multipath-assisted DFL system creates feature vectors at any position based on magnitude and phase measurements of each multipath component (MPC) of the CIR. We evaluate our new approach with a position error probability based on the propagation model including errors, as well as a distance metric of the feature vector of the positions. We compare the performance of the system with a line-of-sight solution with four instead of two nodes and variants of magnitude-only and phase-only approaches. By combining the magnitude and phase measurements of a multipath-assisted DFL system, we achieve a position error probability that is similar to the conventional DFL system.
|||On the Effective Length of Channel Impulse Responses in UWB Single Anchor Localization , In International Conference on Localization and GNSS, 2019. [bib] [abstract]|
Recently, single anchor localization evolves as a new research topic that exploits multipath propagation for calculation of tag positions. With a combination of movement information and particle filters, they provide a precision that is similar to multi-anchor systems. However, a systematic approach to the design and implementation of such systems is not yet available. The combination of theory and mathematical modeling for channel impulse responses is still an open research question that we address in this paper. Therefore, we propose a new representation of a channel impulse response targeted for single anchor localization systems. Based on this representation, we model the relationship between tag positions and channel impulse responses and evaluate the statistic properties of channel impulse responses in this application. In this paper, we introduce a new metric for the assessment of anchor positions, the effective length of CIRs. By the shortest effective length of a set of CIRs, we identify the best anchor position, since it indicates the position where requirements for the measurement of the channel impulse response are lowest.
|||Modeling the Magnitude and Phase of Multipath UWB Signals for the Use in Passive Localization , In 16th Workshop on Positioning, Navigation and Communication, 2019. [bib] [abstract]|
Radio-frequency (RF)-based device-free localization (DFL) systems measure RF parameters such as the received signal strength or channel state information to detect and track objects within a certain area. However, the change of the RF signal caused by the object is superimposed with various changes of the RF signal due to multipath propagation, especially in indoor environments. In this paper, we develop a model for ultra-wideband (UWB) channel impulse response (CIR) measurements for application in DFL systems. The model predicts received signal parameters in a setup with a transmitter and a receiver node, a person and multipath propagation. Different from other approaches, the RF hardware, and the model provides both magnitude and phase information for individual multipath components. We evaluate the new model with real measurements that have been conducted with a Decawave DW1000 radio chip. For the magnitudes, we achieved a correlation factor from 0.78 to 0.87 and maximum mean and standard deviation errors of 1.7 dB and 2.2 dB respectively. For the phase, we achieved correlation factor from 0.6 to 0.81 and maximum mean and standard deviation errors of 0.32 dB and 0.47 dB respectively, showing that the prediction of our proposed model for the magnitude and phase fits well to our measurements.
|||Understanding and Prediction of Ultra-Wide Band Channel Impulse Response Measurements , Technical report, Technische Universität Braunschweig, 2019. [bib] [pdf] [abstract]|
Recently, ultra-wide band transceiver systems have provided data transfer, timestamps and channel impulse response measurements to the user. The interpretation of the timestamps and the channel impulse response, however, is difficult and not intuitive. In simple scenarios, line of sight and non-line of sight pulses can be distinguished easily, which simplifies the reconstruction. For more complex scenarios, the interpretation remains difficult and is still an unsolved problem. In this paper, we investigate the channel impulse response measurements of the DecaWave DW1000 ultra-wide band transceiver and model the expected results for simple scenarios based on information provided from the transceiver data sheet. We will show that we are able to predict the measurement results of the transceiver with acceptable accuracy by applying the model above in experiments.