A Joint TDOA-PDOA Localization Approach Using Particle Swarm Optimization

Hui Chen, Tarig Ballal, Nasir Saeed, Mohamed Slim Alouini, Tareq Y. Al-Naffouri

Research output: Contribution to journalArticlepeer-review

52 Citations (Scopus)

Abstract

Estimating the location of a target Is essential for many applications such as asset tracking, navigation, and data communications. Time-difference-of-arrival (TDOA) based localization has the main advantage that It does not require synchronization between the transmitting and the receiving sides. Phase-difference-of-arrival (PDOA) provides additional Information that can be leveraged to enhance localization performance. The combination of TDOA and PDOA for localization has not been reported In the literature. In this letter, we propose a novel approach that Incorporates both TDOA and PDOA to achieve Improved position estimation. In the proposed approach, an Initial location estimate Is obtained by optimizing a TDOA cost function. Next, a PDOA, or a hybrid TDOA-PDOA cost function Is optimized using a particle swarm optimizer to obtain the final location estimate. Simulation results show that the proposed approach sufficiently, and justifiably, Improves localization performance relative to pure TDOA methods.

Original languageEnglish
Article number9062333
Pages (from-to)1240-1244
Number of pages5
JournalIEEE Wireless Communications Letters
Volume9
Issue number8
DOIs
Publication statusPublished - Aug 2020
Externally publishedYes

Keywords

  • Localization
  • particle swarm optimizer
  • PDOA
  • TDOA

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'A Joint TDOA-PDOA Localization Approach Using Particle Swarm Optimization'. Together they form a unique fingerprint.

Cite this