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Difference between revisions of "Ultra-wideband Concurrent Ranging"

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(Prerequisites)
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== Prerequisites ==
 
== Prerequisites ==
* Strong interest in computer architecture
+
* Strong interest in embedded systems
* Experience with digital design in SystemVerilog as taught in VLSI I
+
* Experience with data acquisition and analysis
* Experience with low-level programming
+
* Experience with low-level C programming
 
 
  
 
= References =
 
= References =

Revision as of 23:07, 18 January 2022


Overview

Status: Available

Introduction

UWB Localization

Ultra-wideband (UWB) is one of the most promising and adopted ranging (i.e., distance measuring) technologies used for positioning and localization, as it enables centimeter-precision distance estimation and data transmission. In our applications, we use UWB with the time-of-arrival (ToA) technique, which determines the distance between two UWB nodes based on the travel time of a radio signal from the transmitter to the receiver. Due to its high-precision ranging, UWB enables range-based localization. The figure in right illustrates the classical UWB localization scenario, where a tag (or more) receives distance (range) measurements from fixed nodes with known positions, called anchors. Knowing the positions of the anchors and the values of the distances to each anchor, the tag can determine its own position. However, in the classical UWB ranging scheme, only two UWB nodes can perform ranging (i.e., distance measurement) at one time: in this example, one anchor with one node. Therefore, in this localization scenario, Tag 0 performs ranging with each anchor, and only then Tag 1 starts ranging with the anchors. The drawback of this scheme is that it can not accommodate a very large number of tags, otherwise the rate of receiving measurements for each individual tag would significantly decrease. To mitigate this issue, this project tackles the concurrent ranging problem, where more UWB nodes can perform ranging at the same time and advanced signal processing and learning algorithms separate the messages of each sender from the received signal.

Project

Character

  • 20% Literature / familiarization with UWB
  • 30% Bare-metal / FreeRTOS C programming
  • 30% Signal processing / machine learning
  • 20% Evaluation

Prerequisites

  • Strong interest in embedded systems
  • Experience with data acquisition and analysis
  • Experience with low-level C programming

References