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Item type:Publication, Access status: without files , Joint Multitarget Tracking and Dynamic Network Localization in the Underwater DomainThis paper addresses the problem of multitarget tracking using a network of mobile sensors with unknown positions. In contrast to commonly-used approaches which split the sensor localization and target tracking into two different sub-problems, we propose a holistic approach for joint localization and tracking. The theory of graphical models is used to describe the statistical relationship between sensors, targets, and measurements. To jointly infer the states of sensors and targets, we use the statistical processing of belief propagation.Publicationtype: Conference Paper64 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Position estimation in networks with sparse infrastructure(2020-04-20); This thesis considers radio-based positioning in the context of sparse infrastructure. The following two approaches have been considered: Cooperative positioning and single-anchor positioning. Theoretical studies have been conducted and positioning algorithms were developed. The results of this thesis show that the considered approaches allow for precise position estimation despite the sparsity of infrastructure.Publicationtype: Doctoral Thesis358 296 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , On the feasibility of situational awareness in millimeter wave massive MIMO systems(2020); ; Situational awareness in wireless networks refers to the availability of information on the states of mobile devices and their propagation environments. Recent studies have shown that the position, orientation, and clock offset of a mobile device can be estimated jointly with a map of reflecting or scattering features in the propagation environment based on the link to a single base station. Yet, it is unknown how important system parameters such as the bandwidth, the number of antennas, and the signal-to-noise ratio affect the estimation accuracy and hence the feasibility of situational awareness. We address this open question by studying the Cramér-Rao lower bound of the joint estimation problem. Particularly, we provide an analytical expression for the corresponding Fisher information matrix and inspect the Cramér-Rao lower bound via numerical simulations. Our results reveal the following insights. First, the reflection loss of objects in the propagation environment has a profound impact on the estimation accuracy of the states of mobile devices and their maps. Second, the massiveness of arrays is a key enabler for accurate state and map estimation and finally, the geometry of the scenario affects the estimation accuracy profoundly.Publicationtype: Conference Paper27 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Enabling Situational Awareness in Millimeter Wave Massive MIMO Systems(2019-09); ; ; Situational awareness in wireless networks refers to the availability of position information on transmitters and receivers as well as information on their propagation environments to aid wireless communications. In millimeter wave massive multiple-input multiple-output communication systems, situational awareness can significantly improve the quality and robustness of communications. In this paper, we establish a model that describes the statistical dependencies between channel state information and the position, orientation, and clock offset of a user equipment along with the locations of features in the propagation environment. Based on this model, we introduce COMPAS (COncurrent Mapping, Positioning, And Synchronization); an inference engine that can provide accurate and reliable situational awareness in millimeter wave massive multiple-input multiple-output communication systems. Numerical results show that COMPAS is able to infer the positions of an unknown and time-varying number of features in the propagation environment and, at the same time, estimate the position, orientation, and clock offset of a user equipment.Publicationtype: Journal Article344 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Fast Inference for Situational Awareness in 5G Millimeter Wave Massive MIMO Systems(2019-08-29); ; ; Publicationtype: Conference Paper174 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Localization, Mapping, and Synchronization in 5G Millimeter Wave Massive MIMO Systems(2019-08-29); ; ; Publicationtype: Conference Paper317 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Joint Localization and Mapping Through Millimeter Wave MIMO in 5G Systems(2019-02-20); ; Millimeter wave signals with multiple transmit and receive antennas are considered as enabling technology for enhanced mobile broadband services in 5G systems. While this combination is mainly associated with achieving high data rates, it also offers huge potential for radio-based positioning. Recent studies showed that millimeter wave signals with multiple transmit and receive antennas are capable of jointly estimating the position and orientation of a mobile terminal while mapping the radio environment simultaneously. To this end, we present a message passing-based estimator which jointly estimates the position and orientation of the mobile terminal, as well as the location of reflectors or scatterers in the absence of the line-of-sight path. We provide numerical examples showing that our estimator can provide considerably higher estimation accuracy compared to a state-of-the-art estimator. Our examples demonstrate that our message passing-based estimator neither requires the presence of a line-of-sight path nor prior knowledge regarding any of the parameters to be estimated.Publicationtype: Conference Paper209 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Position-Constrained Stochastic Inference for Cooperative Indoor Localization(2019-02-13); Publicationtype: Journal Article119 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Harnessing NLOS Components for Position and Orientation Estimation in 5G Millimeter Wave MIMO(2019-01); ; ; In the past, NLOS propagation was proven to be a source of distortion for radio-based positioning systems due to the lack of temporal and spatial resolution of previous cellular systems. Hence, every NLOS component was perceived as a perturbation for localization. Even though 5G is not yet standardized, a strong proposal, which has the potential to overcome the problem of limited temporal and spatial resolution, is the massive MIMO millimeter wave technology. We reconsider the role of NLOS components for position and orientation estimation in 5G millimeter wave MIMO systems. Our analysis is based on the concept of Fisher information. We show that for sufficiently high temporal and spatial resolution, NLOS components always provide position and orientation information that consequently increase position and orientation estimation accuracy. In addition, we show that the information gain of NLOS components depends on the actual location of the reflector or scatter. Our numerical examples suggest that the NLOS components are most informative about the position and orientation of a mobile terminal when the corresponding reflectors or scatterers are illuminated with narrow beams.Publicationtype: Journal Article206 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Error bounds for terahertz MIMO positioning of swarm UAVs for distributed sensingDistributed sensing, where multiple observations from spatially separated antennas are combined, offers many advantages over conventional sensing techniques. The recent advances in the field of unmanned aerial vehicles give rise to an entirely new field of application of distributed sensing. We consider a swarm of unmanned aerial vehicles, where each node of the swarm is equipped with one or multiple antennas, and the swarm senses a target signal collaboratively. With such a swarm, the most compelling feature is that the virtual aperture formed by all the nodes of the swarm is mobile and can be reconfigured. It is well known from the field of distributed sensing that the position of every antenna of the virtual aperture needs to be known precisely to coherently combine the sensed signal. Hence the position of every unmanned aerial vehicle must be determined up to fractions of the sensing wavelength. In order to achieve such a high position accuracy, we consider multiple input multiple output links between nodes, which use orthogonal frequency division multiplexing signals in the terahertz band. We analyze the position and orientation estimation capabilities of such links with respect to the bandwidth, array size, and transmitter-receiver separation. We provide numerical results which reveal the conditions required for millimeter- level positioning accuracy.Publicationtype: Conference Paper133