Vehicle Localization utilizing a Novel Hybrid TDOA-Based Estimation

Oscar Owen*, Zhenni Pan, Shigeru Shimamoto

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This research investigates the use of a hybrid technique to locate vehicle positions on a 2D plane solely via other vehicles to further the future realization of Vehicle-to-Vehicle (V2V) communication. An approach in which trilateration and Time Difference Of Arrival (TDOA) are combined to estimate the Direction Of Arrival (DOA) of an incoming signal is considered. By using TDOA measurements of receivers on the Receiver Vehicle (RV), estimation regions are constructed to robustly obtain the Transmitter Vehicle (TV) position. This proposal not only creates a method for TDOA to be directly used in V2V communication but compared to other localization methods such as TOA (Time Of Arrival), the proposed technique does not need to consider time synchronization between the TV and RV, allowing for usage in a larger variety of on-road scenarios. A regression model is also implemented to further improve the accuracy of the estimation. Evaluation of the proposal is conducted for same side DOA and opposing side DOA. The DOA estimation was compared with a theoretically ideal scenario incorporating TOA. For further clarification of the methods utility and to mimic the transmission signal in road environments, the proposal is also tested in a ray tracing propagation model. The simulations show that the proposed solution accompanied with the regression model estimated the DOA in a 1 nanosecond (ns) time step environment to 1.92° accuracy and 0.08°accuracy in a 0.1ns time step environment.

Original languageEnglish
Title of host publication2022 IEEE 96th Vehicular Technology Conference, VTC 2022-Fall 2022 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665454681
DOIs
Publication statusPublished - 2022
Event96th IEEE Vehicular Technology Conference, VTC 2022-Fall 2022 - London, United Kingdom
Duration: 2022 Sept 262022 Sept 29

Publication series

NameIEEE Vehicular Technology Conference
Volume2022-September
ISSN (Print)1550-2252

Conference

Conference96th IEEE Vehicular Technology Conference, VTC 2022-Fall 2022
Country/TerritoryUnited Kingdom
CityLondon
Period22/9/2622/9/29

Keywords

  • DOA
  • Localization
  • TDOA
  • TOA
  • Trilateration
  • V2V

ASJC Scopus subject areas

  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Applied Mathematics

Fingerprint

Dive into the research topics of 'Vehicle Localization utilizing a Novel Hybrid TDOA-Based Estimation'. Together they form a unique fingerprint.

Cite this