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45 results on '"Siebler, Benjamin"'

1. Empirical Fading Model and Bayesian Calibration for Multipath-Enhanced Device-Free Localization

Author

Schmidhammer, Martin, Gentner, Christian, Walter, Michael, Sand, Stephan, Siebler, Benjamin, and Fiebig, Uwe-Carsten

Subjects
Electrical Engineering and Systems Science - Signal Processing
Abstract

The performance of multipath-enhanced device-free localization severely depends on the information about the propagation paths within the network. While known for the line-of-sight, the propagation paths have yet to be determined for multipath components. This work provides a novel Bayesian calibration approach for determining the propagation paths by estimating reflection points. Therefore, first a statistical fading model is presented, that describes user-induced changes in the received signal of multipath components. The model is derived and validated empirically using an extensive set of wideband and ultra-wideband measurement data. Second, the Bayesian approach is presented, which, based on the derived empirical fading model, relates measured changes in the power of a multipath component to the location of the reflection point. Exploiting the geometric properties of multipath components caused by single-bounce reflections, the solution space of possible locations of reflection points is constrained to the delay ellipse. Thus, a one-dimensional elliptic estimation problem can be formulated, which is solved using a point mass filter. The applicability of the proposed approach is demonstrated and evaluated based on measurement data. Independent of the underlying measurement system, the Bayesian calibration approach is shown to robustly estimate the locations of the reflection points in different environments., Comment: 14 pages, 9 figures

Published
2022
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4. Empirical Fading Model and Bayesian Calibration for Multipath-Enhanced Device-Free Localization

Author

Schmidhammer, Martin, Gentner, Christian, Walter, Michael, Sand, Stephan, Siebler, Benjamin, and Fiebig, Uwe-Carsten

Abstract

MDFL systems determine presence and location of objects and users not necessarily equipped with localization devices. For localization, multipath-enhanced device-free localization (MDFL) systems exploit user-induced changes in the power of all received signal components, including both line-of-sight and multipath components (MPCs). In this work, we therefore provide a statistical fading model that describes user-induced changes in received power specifically for MPCs. The model is derived and validated empirically using an extensive set of wideband and ultra-wideband measurement data. Since the localization performance of MDFL systems strongly depends on the information about the propagation paths within the wireless network, we further propose a Bayesian calibration approach that estimates the location of the reflection points of MPCs caused by single-bounce reflections. For MPCs caused by single-bounce reflections, the solution space of possible locations of reflection points is constrained to the delay ellipse, which allows the formulation of a computationally efficient one-dimensional estimation problem. Eventually, the problem is solved by sequential Bayesian estimation. The applicability of the proposed approach is demonstrated and evaluated using measurement data. Independent of the underlying measurement system, the Bayesian calibration approach is shown to robustly estimate the locations of the reflection points in different environments. Finally, the localization results of MDFL for an indoor scenario confirm the applicability of the Bayesian calibration approach.

Published
2024
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14. Bayesian Cramer-Rao Lower Bound for Magnetic Field-based Localization

Author

Siebler, Benjamin, Sand, Stephan, and Hanebeck, Uwe D.

Subjects
particle filter, indoor localization, Bayesian Cramér-Rao lower bound, DATA processing & computer science, ddc:004, finger-printing, Gaussian process, magnetic field-based localization
Abstract

Magnetic field-based localization is a finger-printing technique using position-dependent distortions of the Earth magnetic field that enables localization in GNSS-denied areas like indoor environments. In addition, magnetic localization is passive and does not require dedicated devices in the infrastructure as it would be the case for comparable RF-based techniques. In this paper, we show how to analyze the achievable position accuracy of magnetic localization based on Bayesian Cramer-Rao lower bounds. The derivation of the bound requires an analytical model, e.g., a map or database, that links the position that is to be estimated to the corresponding magnetic field value. Unfortunately, finding an analytical model from the laws of physics in not feasible due to the complexity of the involved differential equations and the required knowledge about the environment. In this paper, we therefore use a Gaussian process (GP) that approximates the true analytical model based on training data. The GP ensures a smooth, differentiable likelihood and allows a strict Bayesian treatment of the estimation problem. Based on measurements in an indoor environment, the bound is evaluated for different sensor heights and is compared to the mean squared error of a particle filter. Furthermore, the bound is calculated for the case when only the magnetic magnitude is used for positioning and the case when the whole vector field is considered. For both cases, the resulting position bound is below 10 cm indicating an high potential accuracy of magnetic localization.

Published
2022

19. Radio Interference Measurements for Urban Cooperative Intelligent Transportation Systems

Author

Sand, Stephan, primary, Unterhuber, Paul, additional, Ahmed, Dina Bousdar, additional, De Ponte Muller, Fabian, additional, Lehner, Andreas, additional, Rashdan, Ibrahim, additional, Schmidhammer, Martin, additional, Karasek, Rostislav, additional, Siebler, Benjamin, additional, Heirich, Oliver, additional, Gentner, Christian, additional, Walter, Michael, additional, Kaiser, Susanna, additional, Ulmschneider, Markus, additional, Schaab, Marius, additional, Wientgens, Luis, additional, and Strang, Thomas, additional

Published
2021
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20. Bayesian Approaches to Multipath-Enhanced Device-Free Localization

Author

Schmidhammer, Martin, Siebler, Benjamin, Gentner, Christian, Sand, Stephan, and Fiebig, Uwe-Carsten

Subjects
particle filter, Wireless network, Computer science, 020208 electrical & electronic engineering, extended Kalman filter, Sequential Bayesian estimation, Location awareness, 020206 networking & telecommunications, 02 engineering and technology, Filter (signal processing), device-free localization, point mass filter, computer.software_genre, Signal, Power (physics), Nonlinear system, 0202 electrical engineering, electronic engineering, information engineering, Particle filter, computer, Algorithm, Multipath propagation
Abstract

Device-free localization systems infer presence and location of moving users by measuring user-induced perturbations in the signal power between wireless network nodes. Thereby, users not only induce perturbations to the power of the line-of-sight, but also to the power of reflected and scattered signals which are observed in the received signal as multipath components. Since the propagation paths of multipath components differ inherently from the line-of-sight path, these propagation paths can be considered as additional network links. This extended network determines the multipath-enhanced device-free localization system. Based on empirical models that relate perturbations in the power of multipath components to the user location, the localization problem can be solved by nonlinear Bayesian filtering. In this work, we therefore investigate the point mass filter and the particle filter as possible solutions. Using simulations, we demonstrate the applicability of these filter solutions for multipath-enhanced device-free localization. The overall localization performance is comparable for both filters. Further, the simulation results indicate an improvement of the localization performance of multipath-enhanced device-free localization compared to device-free localization.

Published
2021

21. Radio Interference Measurements for Urban Cooperative Intelligent Transportation Systems

Author

Sand, Stephan, Unterhuber, Paul, Bousdar Ahmed, Dina, Ponte Müller, Fabian, Lehner, Andreas, Rashdan, Ibrahim, Schmidhammer, Martin, Karasek, Rostislav, Siebler, Benjamin, Heirich, Oliver, Gentner, Christian, Walter, Michael, Kaiser, Susanna, Ulmschneider, Markus, Schaab, Marius, Wientgens, Luis, and Strang, Thomas

Subjects
LTE C-V2X, ITS-G5, GNSS, C-ITS, CBTC, channel sounding, interference measurements, IEEE 802.11a
Published
2021

22. 802.11bd NGV Ranging Status and Types

Author

Sand, Stephan, Unterhuber, Paul, Siebler, Benjamin, Schmidhammer, Martin, Ponte Müller, Fabian, Lehner, Andreas, Berens, Friedbert, Sarris, Ioannis, Schiessl, Sebastian, Sadeghi, Bahar, Segev, Jonathan, and Li, Qinghua

Subjects
NGV, FTM, EDCA, TOF, Passive TB ranging, TB ranging, IEEE 802.11bd, TOA, ranging, RTT, NTB ranging, differential distance computation
Published
2020

26. Consideration on Ranging in NGV

Author

Sand, Stephan, Unterhuber, Paul, Siebler, Benjamin, Soliman, Mohammad, Schmidhammer, Martin, and De Ponte Müller, Fabian

Subjects
bandwidth, ranging, train-to-train propagation measurements and ranging, 60 GHz, 802.11bd, lower bounds, waveform, next generation V2X (NGV), Nachrichtensysteme, TOA, numerologies, ZZB, RTD, 5.9 GHz, CRLB, radar
Abstract

Considerations on Ranging in NGV given PAR and use case baseline: * Analysis method: Lower Bounds * Observation model: AWGN and line of sight (LOS) free space path loss * 5.9 GHz band: - Waveform analysis - Time-of-arrival (TOA) vs. round-trip-delay (RTD) ranging - Bandwidth and different numerologies * 60 GHz band: - Comparison between RTD ranging and Radar - Dynamic Train-to-Train Propagation Measurements and ranging results

Published
2019

28. Localization of Discrete Mobile Scatterers in Vehicular Environments Using Delay Estimates

Author

Schmidhammer, Martin, Gentner, Christian, and Siebler, Benjamin

Subjects
Mulitlateration, 050210 logistics & transportation, Optimization problem, Estimation theory, Computer science, 05 social sciences, Levenberg-Marquard, 020206 networking & telecommunications, 02 engineering and technology, Least squares, localization, KEST, non-linear least-squares, Non-linear least squares, 0502 economics and business, 0202 electrical engineering, electronic engineering, information engineering, Nachrichtensysteme, Link level, Wideband, parameter estimation, Algorithm, Multipath propagation
Abstract

This paper presents a localization approach which aims to detect and localize discrete mobile scatterers. Therefore, a network of spatially distributed transmitting and receiving nodes is used. The localization problem is formulated as a non-linear optimization problem and corresponding performance bounds for the positioning error are provided. To solve the optimization problem, an iterative non-linear least squares approach is used, following the algorithm of Levenberg and Marquard. The proposed localization approach is evaluated based on wideband measurement data. It is shown, that the localization of mobile scatterers can be achieved. A further evaluation reveals a strong dependence of the localization performance on the preceding link level parameter estimation. Particularly sparse networks are shown to be sensitive to rich multipath environments.

Published
2019

34. Study of Train-Side Passive Magnetic Measurements with Applications to Train Localization

Author

Heirich, Oliver, Siebler, Benjamin, Hedberg, Erik, Heirich, Oliver, Siebler, Benjamin, and Hedberg, Erik

Abstract

Passive magnetic sensors measure the magnetic field density in three axes and are often integrated on a single chip. These low-cost sensors are widely used in car navigation as well as in battery powered navigation equipment such as smartphones as part of an electronic compass. We focus on a train localization application with multiple, exclusively onboard sensors and a track map. This approach is considered as a base technology for future railway applications such as collision avoidance systems or autonomous train driving. In this paper, we address the following question: how beneficial are passive magnetic measurements for train localization? We present and analyze measurements of two different magnetometers recorded on a regional train at regular passenger service. We show promising correlations of the measurements with the track positions and the traveled switch way. The processed data reveals that the railway environment has repeatable, location-dependent magnetic signatures. This is considered as a novel approach to train localization, as the use of these magnetic signals at first view is not obvious. The proposed methods based on passive magnetic measurements show a high potential to be integrated in new and existing train localization approaches.

Published
2017
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