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Found 16 papers, 1 papers with code
Integrated Monostatic and Bistatic mmWave Sensing
Millimeter-wave (mmWave) signals provide attractive opportunities for sensing due to their inherent geometrical connections to physical propagation channels.
Set-Type Belief Propagation with Applications to Poisson Multi-Bernoulli SLAM
In this paper, we develop BP rules for factor graphs defined on sequences of RFSs where each RFS has an unknown number of elements, with the intention of deriving novel inference methods for RFSs.
Simultaneous Localization and Mapping
Vocal Bursts Type Prediction
Experimental Validation of Single BS 5G mmWave Positioning and Mapping for Intelligent Transport
Positioning with 5G signals generally requires connection to several base stations (BSs), which makes positioning more demanding in terms of infrastructure than communications.
RISs and Sidelink Communications in Smart Cities: The Key to Seamless Localization and Sensing
A smart city involves, among other elements, intelligent transportation, crowd monitoring, and digital twins, each of which requires information exchange via wireless communication links and localization of connected devices and passive objects (including people).
Modeling and Analysis of OFDM-based 5G/6G Localization under Hardware Impairments
Our extensive simulation results demonstrate that each type of HWI leads to a different level of degradation in angle and delay estimation performance, and the prominent impairment factors on delay estimation will have a dominant negative effect on SER.
RIS-Aided Monostatic Sensing and Object Detection with Single and Double Bounce Multipath
We propose a framework for monostatic sensing by a user equipment (UE), aided by a reconfigurable intelligent surface (RIS) in environments with single- and double-bounce signal propagation.
RIS-Enabled and Access-Point-Free Simultaneous Radio Localization and Mapping
In the upcoming sixth generation (6G) of wireless communication systems, reconfigurable intelligent surfaces~(RISs) are regarded as one of the promising technological enablers, which can provide programmable signal propagation.
MmWave Mapping and SLAM for 5G and Beyond
We distinguish the different types of sensing problems and then focus on mapping and SLAM as running examples.
Bayesian Integrity Monitoring for Cellular Positioning -- A Simplified Case Study
Bayesian receiver autonomous integrity monitoring (RAIM) algorithms are developed for the snapshot cellular positioning problem in a simplified one-dimensional (1D) linear Gaussian setting.
Doppler-Enabled Single-Antenna Localization and Mapping Without Synchronization
With the help of multipath components (MPCs), localization and mapping tasks can be done with a single base station (BS) and single unsynchronized user equipment (UE) if both of them are equipped with an antenna array.
PMBM-based SLAM Filters in 5G mmWave Vehicular Networks
Secondly, the Poisson multi-Bernoulli (PMB) SLAM filter is based on the standard reduction from PMBM to PMB, but involves a novel interpretation based on auxiliary variables and a relation to Bethe free energy.
A Computationally Efficient EK-PMBM Filter for Bistatic mmWave Radio SLAM
Millimeter wave (mmWave) signals are useful for simultaneous localization and mapping (SLAM), due to their inherent geometric connection to the propagation environment and the propagation channel.
Dirichlet process approach for radio-based simultaneous localization and mapping
By comparing the results with the SLAM based on the Rao-Blackwellized probability hypothesis density filter, we confirm a slight drop in SLAM performance, but as a result, we validate that it has a significant gain in computational complexity.
Cooperative mmWave PHD-SLAM with Moving Scatterers
Using the multiple-model (MM) probability hypothesis density (PHD) filter, millimeter wave (mmWave) radio simultaneous localization and mapping (SLAM) in vehicular scenarios is susceptible to movements of objects, in particular vehicles driving in parallel with the ego vehicle.
Exploiting Diffuse Multipath in 5G SLAM
5G millimeter wave (mmWave) signals can be used to jointly localize the receiver and map the propagation environment in vehicular networks, which is a typical simultaneous localization and mapping (SLAM) problem.
5G mmWave Cooperative Positioning and Mapping using Multi-Model PHD Filter and Map Fusion
5G millimeter wave (mmWave) signals can enable accurate positioning in vehicular networks when the base station (BS) and vehicles are equipped with large antenna arrays.
