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Localization algorithms for asynchronous time difference of arrival positioning systems.

Shuai He1, Xiaodai Dong1, Wu-Sheng Lu1

  • 1Department of Electrical and Computer Engineering, University of Victoria, 3800 Finnerty Road, Victoria, V8P 5C2 Canada.

EURASIP Journal on Wireless Communications and Networking
|February 28, 2020
PubMed
Summary
This summary is machine-generated.

This study introduces a practical asynchronous time difference of arrival (ATDOA) positioning system. New algorithms and a receiver re-selection method enhance localization accuracy and performance in realistic indoor environments.

Keywords:
Asynchronous positioning systemsConstrained least-squaresCramer-Rao lower bound (CRLB)LocalizationSemidefinite programming (SDP)Taylor seriesTime difference of arrival (TDOA)

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Area of Science:

  • Signal Processing
  • Localization Systems
  • Wireless Communication

Background:

  • Asynchronous Time Difference of Arrival (ATDOA) positioning offers practical advantages due to its lack of time synchronization requirements.
  • Existing ATDOA systems can benefit from improved localization algorithms and receiver selection strategies.

Purpose of the Study:

  • To present a novel ATDOA localization model and introduce two new localization algorithms.
  • To develop a receiver re-selection method for enhanced estimation accuracy.
  • To derive the Cramer-Rao lower bound (CRLB) for ATDOA systems with realistic noise models.

Main Methods:

  • A two-step positioning algorithm combining semidefinite programming (SDP) and Taylor series expansion.
  • A constrained least-squares method for low-complexity, fast convergence localization.
  • Development of a novel receiver re-selection technique.
  • Derivation of CRLB using a distance-dependent noise variance model.

Main Results:

  • The SDP-Taylor series algorithm achieves global convergence and superior accuracy.
  • The constrained least-squares method demonstrates low complexity and fast convergence with good performance.
  • The receiver re-selection method significantly improves estimation accuracy.
  • The derived CRLB accurately models realistic indoor propagation channels.

Conclusions:

  • The proposed ATDOA localization model, algorithms, and receiver re-selection method offer significant improvements in practical positioning systems.
  • The study provides a theoretical bound (CRLB) for performance evaluation in realistic scenarios.