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Local Wireless Sensor Networks Positioning Reliability Under Sensor Failure.

Javier Díez-González1, Rubén Álvarez2, Natalia Prieto-Fernández1

  • 1Department of Mechanical, IT and Aerospace Engineering, Universidad de León, 24071 León, Spain.

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|March 11, 2020
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Summary
This summary is machine-generated.

This study introduces a new sensor deployment for Time Difference of Arrival (TDOA) systems, improving autonomous navigation robustness. The method enhances localization accuracy and convergence region size, even with sensor failures.

Keywords:
LPScramer rao lower boundlocalizationmulti-objective optimizationsensor failurewireless sensor networks

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Area of Science:

  • Robotics and Autonomous Systems
  • Sensor Networks
  • Navigation and Positioning

Background:

  • Local Positioning Systems (LPS) are crucial for autonomous navigation, especially in challenging environments.
  • Time Difference of Arrival (TDOA) methods offer robust localization but can be sensitive to sensor failures.
  • Ensuring system availability during sensor malfunction is a key research challenge.

Purpose of the Study:

  • To develop a novel sensor deployment methodology for TDOA localization systems.
  • To guarantee system availability and robustness against single sensor failures.
  • To optimize node placement for a balance between normal operation and failure scenarios.

Main Methods:

  • A five-node TDOA localization method is employed.
  • A strategy to resolve ambiguity in four-sensor TDOA configurations is implemented by maximizing solution distance.
  • Genetic Algorithm Optimization is used with Cramer-Rao Lower Bound derivation to optimize node locations.

Main Results:

  • The proposed optimization, considering sensor failure, improves average convergence region size by 31% and location accuracy by 22% under malfunction.
  • Normal operating conditions experience less than a 5% reduction in accuracy.
  • The methodology effectively enhances system resilience to sensor failures.

Conclusions:

  • The developed sensor deployment methodology significantly improves the reliability of TDOA-based autonomous navigation systems.
  • Optimizing for sensor failure provides a robust trade-off between performance under normal and degraded conditions.
  • This approach is vital for high-demand applications requiring continuous and accurate positioning.