@article{32165, abstract = {{This article presents analyses of excerpts from a study on writing conducted in a dialogical perspective. The study’s material was collected by the auto-confrontation method: writers were videotaped during their work and afterwards confronted with their writing activities. Microanalysis of the material attends to how inner dialogues during writing are “refracted” (Voloshinov) in auto-confrontation. Bakhtin’s notion of the chronotope (time-and-space) as the main tool of analysis helps to discern the changing contexts and position constellations utterances are valid for. It thus sheds light on the positioning movements performed by the writing selves through language. The analyses show various utterance movements traversing the chronotopes involved, ranging from refractions of movements between the writers’ inner dialogues and their texts to retrospective imperatives with a developmental potential. This “dialogical volume” of speech activity presenting itself in writing can contribute to our understanding of the interplay of language and the self.}}, author = {{Karsten, Andrea}}, issn = {{0959-3543}}, journal = {{Theory & Psychology}}, keywords = {{auto-confrontation, chronotope, inner dialogue, microanalysis, positioning, writing}}, number = {{4}}, pages = {{479--503}}, publisher = {{SAGE Publications}}, title = {{{Writing: Movements of the self}}}, doi = {{10.1177/0959354314541020}}, volume = {{24}}, year = {{2014}}, } @inproceedings{11816, abstract = {{In this paper, we consider the Maximum Likelihood (ML) estimation of the parameters of a GAUSSIAN in the presence of censored, i.e., clipped data. We show that the resulting Expectation Maximization (EM) algorithm delivers virtually biasfree and efficient estimates, and we discuss its convergence properties. We also discuss optimal classification in the presence of censored data. Censored data are frequently encountered in wireless LAN positioning systems based on the fingerprinting method employing signal strength measurements, due to the limited sensitivity of the portable devices. Experiments both on simulated and real-world data demonstrate the effectiveness of the proposed algorithms.}}, author = {{Hoang, Manh Kha and Haeb-Umbach, Reinhold}}, booktitle = {{38th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013)}}, issn = {{1520-6149}}, keywords = {{Gaussian processes, Global Positioning System, convergence, expectation-maximisation algorithm, fingerprint identification, indoor radio, signal classification, wireless LAN, EM algorithm, ML estimation, WiFi indoor positioning, censored Gaussian data classification, clipped data, convergence properties, expectation maximization algorithm, fingerprinting method, maximum likelihood estimation, optimal classification, parameters estimation, portable devices sensitivity, signal strength measurements, wireless LAN positioning systems, Convergence, IEEE 802.11 Standards, Maximum likelihood estimation, Parameter estimation, Position measurement, Training, Indoor positioning, censored data, expectation maximization, signal strength, wireless LAN}}, pages = {{3721--3725}}, title = {{{Parameter estimation and classification of censored Gaussian data with application to WiFi indoor positioning}}}, doi = {{10.1109/ICASSP.2013.6638353}}, year = {{2013}}, } @inproceedings{11726, abstract = {{In this paper we present a robust location estimation algorithm especially focused on the accuracy in vertical position. A loosely-coupled error state space Kalman filter, which fuses sensor data of an Inertial Measurement Unit and the output of a Global Positioning System device, is augmented by height information from an altitude measurement unit. This unit consists of a barometric altimeter whose output is fused with topographic map information by a Kalman filter to provide robust information about the current vertical user position. These data replace the less reliable vertical position information provided the GPS device. It is shown that typical barometric errors like thermal divergences and fluctuations in the pressure due to changing weather conditions can be compensated by the topographic map information and the barometric error Kalman filter. The resulting height information is shown not only to be more reliable than height information provided by GPS. It also turns out that it leads to better attitude and thus better overall localization estimation accuracy due to the coupling of spatial orientations via the Direct Cosine Matrix. Results are presented both for artificially generated and field test data, where the user is moving by car.}}, author = {{Bevermeier, Maik and Walter, Oliver and Peschke, Sven and Haeb-Umbach, Reinhold}}, booktitle = {{7th Workshop on Positioning Navigation and Communication (WPNC 2010)}}, keywords = {{altitude measurement unit, barometers, barometric altimeter, barometric error Kalman filter, barometric height estimation, direct cosine matrix, global positioning system, Global Positioning System, GPS device, height information, height measurement, inertial measurement unit, Kalman filters, loosely-coupled error state space Kalman filter, loosely-coupled Kalman-filter, map matching, robust information, robust location estimation, sensor fusion, topographic map information, vertical user position}}, pages = {{128--134}}, title = {{{Barometric height estimation combined with map-matching in a loosely-coupled Kalman-filter}}}, doi = {{10.1109/WPNC.2010.5650745}}, year = {{2010}}, } @inproceedings{11723, abstract = {{In this paper we present a novel vehicle tracking algorithm, which is based on multi-level sensor fusion of GPS (global positioning system) with Inertial Measurement Unit sensor data. It is shown that the robustness of the system to temporary dropouts of the GPS signal, which may occur due to limited visibility of satellites in narrow street canyons or tunnels, is greatly improved by sensor fusion. We further demonstrate how the observation and state noise covariances of the employed Kalman filters can be estimated alongside the filtering by an application of the Expectation-Maximization algorithm. The proposed time-variant multi-level Kalman filter is shown to outperform an Interacting Multiple Model approach while at the same time being computationally less demanding.}}, author = {{Bevermeier, Maik and Peschke, Sven and Haeb-Umbach, Reinhold}}, booktitle = {{6th Workshop on Positioning Navigation and Communication (WPNC 2009)}}, keywords = {{covariance matrices, expectation-maximisation algorithm, expectation-maximization algorithm, global positioning system, Global Positioning System, GPS, inertial measurement unit, interacting multiple model approach, Kalman filters, multilevel sensor fusion, narrow street canyons, narrow tunnels, online parameter estimation, parameter estimation, road vehicles, robust vehicle localization, sensor fusion, state noise covariances, time-variant multilevel Kalman filter, vehicle tracking algorithm}}, pages = {{235--242}}, title = {{{Robust vehicle localization based on multi-level sensor fusion and online parameter estimation}}}, doi = {{10.1109/WPNC.2009.4907833}}, year = {{2009}}, } @inproceedings{11724, abstract = {{In this paper we present a novel vehicle tracking method which is based on multi-stage Kalman filtering of GPS and IMU sensor data. After individual Kalman filtering of GPS and IMU measurements the estimates of the orientation of the vehicle are combined in an optimal manner to improve the robustness towards drift errors. The tracking algorithm incorporates the estimation of time-variant covariance parameters by using an iterative block Expectation-Maximization algorithm to account for time-variant driving conditions and measurement quality. The proposed system is compared to an interacting multiple model approach (IMM) and achieves improved localization accuracy at lower computational complexity. Furthermore we show how the joint parameter estimation and localizaiton can be conducted with streaming input data to be able to track vehicles in a real driving environment.}}, author = {{Bevermeier, Maik and Peschke, Sven and Haeb-Umbach, Reinhold}}, booktitle = {{IEEE 69th Vehicular Technology Conference (VTC 2009 Spring)}}, keywords = {{computational complexity, expectation-maximisation algorithm, Global Positioning System, inertial measurement unit, inertial navigation, interacting multiple model, iterative block expectation-maximization algorithm, Kalman filters, multi-stage Kalman filter, parameter estimation, road vehicles, vehicle positioning, vehicle tracking}}, pages = {{1--5}}, title = {{{Joint Parameter Estimation and Tracking in a Multi-Stage Kalman Filter for Vehicle Positioning}}}, doi = {{10.1109/VETECS.2009.5073634}}, year = {{2009}}, } @inproceedings{11881, abstract = {{A combination of GPS (global positioning system) and INS (inertial navigation system) is known to provide high precision and highly robust vehicle localization. Notably during times when the GPS signal has a poor quality, e.g. due to the lack of a sufficiently large number of visible satellites, the INS, which may consist of a gyroscope and an odometer, will lead to improved positioning accuracy. In this paper we show how velocity information obtained from GSM (global system for mobile communications) signalling, rather than from a tachometer, can be used together with a gyroscope sensor to support localization in the presence of temporarily unavailable GPS data. We propose a sensor fusion system architecture and present simulation results that show the effectiveness of this approach.}}, author = {{Peschke, Sven and Bevermeier, Maik and Haeb-Umbach, Reinhold}}, booktitle = {{6th Workshop on Positioning Navigation and Communication (WPNC 2009)}}, keywords = {{cellular radio, distance measurement, global positioning system, Global Positioning System, global system for mobile communications, GPS positioning approach, GSM velocity, gyroscopes, gyroscope sensor, inertial navigation, inertial navigation system, odometer, sensor fusion system architecture, sensors}}, pages = {{195--202}}, title = {{{A GPS positioning approach exploiting GSM velocity estimates}}}, doi = {{10.1109/WPNC.2009.4907827}}, year = {{2009}}, } @article{11799, abstract = {{In this paper, we propose a novel similarity measure to be used for localizing mobile terminals by comparing measured signal power levels with a database of predictions. The proposed measure provides the possibility to incorporate inherent information about signal power level measurements requested by the serving base station but not reported by the mobile terminal. Increased positioning accuracy was observed both in simulations and with real field data}}, author = {{Haeb-Umbach, Reinhold and Peschke, Sven}}, journal = {{IEEE Transactions on Vehicular Technology}}, keywords = {{cellular phone positioning, cellular radio, measured signal power levels, mobile handsets, mobility management (mobile radio)}}, number = {{1}}, pages = {{368--372}}, title = {{{A Novel Similarity Measure for Positioning Cellular Phones by a Comparison With a Database of Signal Power Levels}}}, doi = {{10.1109/TVT.2006.889563}}, volume = {{56}}, year = {{2007}}, } @inproceedings{38104, abstract = {{Location-aware services for private use such as GPS- based navigation systems and GSM-based offerings have become quite a success for outdoor applications, while indoor positioning systems are still mainly employed for professional use only. The main reasons are cost issues and the complexity of setup and maintenance of those systems. In this paper we present CaMPTrack (Camera-based Multiple Person Tracker), a prototype of a webcam-based positioning system and discuss its application and development challenges.}}, author = {{Schäfer, Robbie and Müller, Wolfgang and Deimann, Roman and Kleinjohann, Bernd}}, booktitle = {{Proceedings of the Workshop on Mobile Spatial Interaction at CHI 2007}}, keywords = {{Positioning Systems, Camera Based, Cost Efficiency, Smart Home Applications}}, title = {{{A Low-Cost Positioning System for Location-Aware Applications in Smart Homes}}}, year = {{2007}}, } @inproceedings{9519, abstract = {{Several positioning tasks demand translatory drive instead of rotary motion. To achieve drives that are capable e.g. to drive the sunroof of a car or to lift a car's window, multiple miniaturized motors can be combined. But in this case many other questions arise: the electromechanical behavior of the individual motors differs slightly, the motor characteristics are strongly dependent on the driving parameters and the driven load, many applications need some extra power for special cases like overcoming higher forces periodically. Thus, the bundle of motors has to act well organized and controlled to get an optimized drive that is not oversized and costly.}}, author = {{Hemsel, Tobias and Mracek, Maik and Wallaschek, Jörg and Vasiljev, Piotr}}, booktitle = {{Ultrasonics Symposium, 2004 IEEE}}, issn = {{1051-0117}}, keywords = {{drives, electromechanical effects, linear motors, ultrasonic motors, car sunroof, car window, electromechanical behavior, high power ultrasonic linear motors, multiple miniaturized motors, positioning tasks, translatory drive, Costs, Electromagnetic forces, Frequency, Laboratories, Manufacturing, Mechatronics, Micromotors, Ultrasonic imaging, Vibrations, Voltage}}, number = {{Vol.2}}, pages = {{1161--1164}}, title = {{{A novel approach for high power ultrasonic linear motors}}}, doi = {{10.1109/ULTSYM.2004.1417988}}, volume = {{2}}, year = {{2004}}, } @inproceedings{11733, abstract = {{Current navigation systems like GPS (Global Positioning System) and its Russian counterpart GLONASS (Global Navigation Satellite System) only evaluate the direct signal path. The receivers treat the reflected paths also reaching the receiver antenna as disturbance which has to be suppressed. Multipath affects the tracking accuracy by resulting in a degeneration of the S-curve of the DLL (delay locked loop). Nowadays the future European systems GALILEO and GPSIIF/III with two new signals are on the way to the market and it is time to think about new receiver structures. Therefore we investigated if it is possible to use multipath for navigation constructively.}}, author = {{Bischoff, Renke and Haeb-Umbach, Reinhold and Schulz, Wolfgang and Heinrichs, Guenther}}, booktitle = {{IEEE 55th Vehicular Technology Conference (VTC 2002 Spring)}}, keywords = {{combined GALILEO/UMTS receiver, delay locked loop, delay lock loops, DLL, Global Positioning System, GLONASS, GPS, GPSIIF/III, mobile satellite communication, multipath channels, multipath receiver structure, radio receivers, RAKE receiver, S-curve}}, pages = {{1844--1848 vol.4}}, title = {{{Employment of a multipath receiver structure in a combined GALILEO/UMTS receiver}}}, doi = {{10.1109/VTC.2002.1002940}}, volume = {{4}}, year = {{2002}}, }