The accuracy of radio-based positioning systems will be limited by multipath interference in realistic application scenarios. This paper derives closed-form expressions for the Cramér⁻Rao lower bound (CRLB) on the achievable time-of-arrival (ToA) and angle-of-arrival (AoA) estimation-error variances, considering the presence of multipath radio channels, and extends these results to position estimation. The derivations are based on channel models comprising deterministic, specular multipath components as well as stochastic, diffuse/dense multipath. The derived CRLBs thus allow an evaluation of the influence of channel parameters, the geometric configuration of the environment, and system parameters such as signal bandwidth and array geometry. Our results quantify how the ToA and AoA accuracies decrease when the signal bandwidth is reduced, because more multipath will then interfere with the useful LoS component. Antenna arrays can (partly) compensate this performance loss, exploiting diversity among the multipath interference. For example, the AoA accuracy with a 16-element linear array at 1 MHz bandwidth is similar to a two-element array at 1 GHz , in the magnitude order of one degree. The ToA accuracy, on the other hand, still scales by a factor of 100 from the cm-regime to the m-regime because of the dominating influence of the signal bandwidth. The position error bound shows the relationship between the range and angle information under realistic indoor channel conditions and their different scaling behaviors as a function of the anchor⁻agent placement. Specular multipath components have a maximum detrimental influence near the walls. It is shown for an L-shaped room that a fairly even distribution of the position error bound can be achieved throughout the environment, using two anchors equipped with 2 × 2 -array antennas. The accuracy limit due to multipath increases from the 1⁻10-cm-range at 1 GHz bandwidth to the 0.5⁻1-m-range at 100 MHz .
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http://dx.doi.org/10.3390/s18124249 | DOI Listing |
Med Biol Eng Comput
December 2024
School of Mechanical Engineering, Yanshan University, Qinhuangdao, China.
This study focuses on improving the performance of steady-state visual evoked potential (SSVEP) in brain-computer interfaces (BCIs) for robotic control systems. The challenge lies in effectively reducing the impact of artifacts on raw data to enhance the performance both in quality and reliability. The proposed MVMD-MSI algorithm combines the advantages of multivariate variational mode decomposition (MVMD) and multivariate synchronization index (MSI).
View Article and Find Full Text PDFACS Nano
December 2024
Department of Physics, Syracuse University, 201 Physics Building, Syracuse, New York 13244-1130, United States.
Two or more protein ligands may compete against each other to interact transiently with a protein receptor. While this is a ubiquitous phenomenon in cell signaling, existing technologies cannot identify its kinetic complexity because specific subpopulations of binding events of different ligands are hidden in the averaging process in an ensemble. In addition, the limited time resolution of prevailing methods makes detecting and discriminating binding events among diverse interacting partners challenging.
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